Parte 2: Reconocimiento de objetos

Cargamos las imágenes

import os
import numpy as np
from skimage.io import imread
from skimage.color import gray2rgb
from skimage.transform import resize
from skimage import exposure
from scipy.ndimage import rotate, shift

# Rutas de imágenes y máscaras
ruta_imagenes = r"C:\Users\norae\piva_enrique\Materiales1\objects\objects\images"
ruta_mascaras = r"C:\Users\norae\piva_enrique\Materiales1\objects\objects\masks"

# Diccionario de clases simplificado
clases = {
    'elephant': 0,
    'rhino': 1,
    'emu': 2,         # se etiquetará como "otros"
    'flamingo': 2     # también como "otros"
}

# Tamaño objetivo para redimensionar las imágenes
tamaño_objetivo = (200, 300)

# Función para cargar imágenes con su clase
def cargar_imagenes_objeto(ruta_base, clases, tamaño_objetivo):
    imagenes = []
    etiquetas = []

    for nombre_clase in os.listdir(ruta_base):
        if nombre_clase not in clases:
            continue

        etiqueta = clases[nombre_clase]
        ruta_clase = os.path.join(ruta_base, nombre_clase)
        nombres_archivos = sorted(os.listdir(ruta_clase))

        for nombre_archivo in nombres_archivos:
            ruta_imagen = os.path.join(ruta_clase, nombre_archivo)
            imagen = imread(ruta_imagen) / 255.0

            if imagen.ndim == 2:
                imagen = gray2rgb(imagen)

            imagen_redim = resize(imagen, tamaño_objetivo, anti_aliasing=True)
            imagenes.append(imagen_redim)
            etiquetas.append(etiqueta)

    return np.array(imagenes, dtype=np.float32), np.array(etiquetas)

# Función para cargar las máscaras
def cargar_mascaras(ruta_mascaras, clases, tamaño_objetivo):
    mascaras = []

    for nombre_clase in os.listdir(ruta_mascaras):
        if nombre_clase not in clases:
            continue

        ruta_clase = os.path.join(ruta_mascaras, nombre_clase)
        nombres_archivos = sorted(os.listdir(ruta_clase))

        for nombre_archivo in nombres_archivos:
            ruta_mascara = os.path.join(ruta_clase, nombre_archivo)
            imagen = imread(ruta_mascara) / 255.0

            imagen_redim = resize(imagen, tamaño_objetivo)
            mascara_binaria = (imagen_redim > 0.5).astype(np.uint8)
            mascaras.append(mascara_binaria)

    return np.array(mascaras)

# Función para aumentar el dataset 
def aumentar_dataset_manual(imagenes, mascaras, etiquetas, n_augmentaciones=2):
    imagenes_aug = []
    mascaras_aug = []
    etiquetas_aug = []

    for img, mask, label in zip(imagenes, mascaras, etiquetas):
        imagenes_aug.append(img)
        mascaras_aug.append(mask)
        etiquetas_aug.append(label)

        for _ in range(n_augmentaciones):
            img_aug = img.copy()
            mask_aug = mask.copy()

            # Flip horizontal
            if np.random.rand() > 0.5:
                img_aug = np.fliplr(img_aug)
                mask_aug = np.fliplr(mask_aug)

            # Flip vertical
            if np.random.rand() > 0.5:
                img_aug = np.flipud(img_aug)
                mask_aug = np.flipud(mask_aug)

            # Rotación aleatoria
            angle = np.random.uniform(-20, 20)
            img_aug = rotate(img_aug, angle, reshape=False, mode='reflect')
            mask_aug = rotate(mask_aug, angle, reshape=False, mode='nearest')

            # Desplazamiento aleatorio
            shift_x = np.random.uniform(-10, 10)
            shift_y = np.random.uniform(-10, 10)
            img_aug = shift(img_aug, shift=(shift_x, shift_y, 0), mode='reflect')
            mask_aug = shift(mask_aug, shift=(shift_x, shift_y), mode='nearest')

            # Ajuste de brillo/contraste
            if np.random.rand() > 0.5:
                gamma = np.random.uniform(0.8, 1.2)
                img_aug = exposure.rescale_intensity(img_aug, in_range='image', out_range=(0, 1))
                img_aug = exposure.adjust_gamma(img_aug, gamma=gamma)
                img_aug = np.clip(img_aug, 0, 1)

            imagenes_aug.append(img_aug)
            mascaras_aug.append((mask_aug > 0.5).astype(np.uint8))
            etiquetas_aug.append(label)

    return np.array(imagenes_aug), np.array(mascaras_aug), np.array(etiquetas_aug)

# Cargar datos filtrados
imagenes, etiquetas = cargar_imagenes_objeto(ruta_imagenes, clases, tamaño_objetivo)
mascaras = cargar_mascaras(ruta_mascaras, clases, tamaño_objetivo)

# Aumentar el dataset
imagenes_aug, mascaras_aug, etiquetas_aug = aumentar_dataset_manual(imagenes, mascaras, etiquetas, n_augmentaciones=2)

# Verificación
print(f"Número total de imágenes aumentadas: {imagenes_aug.shape[0]}")
indice = 43
print(f"Imagen {indice} - shape: {imagenes[indice].shape}, etiqueta: {etiquetas[indice]}")
print(f"Mascara {indice} - shape: {mascaras[indice].shape}, valores únicos: {np.unique(mascaras[indice])}")

Número total de imágenes aumentadas: 729
Imagen 43 - shape: (200, 300, 3), etiqueta: 0
Mascara 43 - shape: (200, 300), valores únicos: [0 1]

Vemos las imágenes

import matplotlib.pyplot as plt

def mostrar_galeria(imagenes, titulos=None, filas=3, columnas=5, cmap=None, suptitulo=None):
    total = filas * columnas
    fig, axes = plt.subplots(filas, columnas, figsize=(16, 12))

    for i, ax in enumerate(axes.flat):
        if i < len(imagenes):
            imagen = imagenes[i]
            ax.imshow(imagen, cmap=cmap if imagen.ndim == 2 else None)
            if titulos:
                ax.set_title(str(titulos[i]))
            ax.axis('off')
        else:
            ax.axis('off')

    if suptitulo:
        plt.subplots_adjust(top=0.9)
        fig.suptitle(suptitulo, fontsize=18)

    plt.tight_layout()
    plt.show()

# Títulos opcionales
titulos_animales = [f'Clase: {etiquetas[i]}' for i in range(len(imagenes))]
titulos_mascaras = [f'Máscara {i+1}' for i in range(len(mascaras))]

# Visualizar primeras 15 imágenes
mostrar_galeria(imagenes[:15], titulos_animales[:15], filas=3, columnas=5, suptitulo='Imágenes originales')

# Visualizar primeras 15 máscaras
mostrar_galeria(mascaras[:15], titulos_mascaras[:15], filas=3, columnas=5, cmap='gray', suptitulo='Máscaras binarizadas')

Extraemos las características del espacio RGB

def obtener_medias_rgb(imagenes, mascaras):
    caracteristicas_figura = []
    caracteristicas_fondo = []

    for idx in range(len(imagenes)):
        img = imagenes[idx]
        mask = mascaras[idx]

        # Separar canales RGB
        r, g, b = img[:, :, 0], img[:, :, 1], img[:, :, 2]

        # Índices booleanos para figura (1) y fondo (0)
        indices_figura = mask == 1
        indices_fondo = mask == 0

        # Evitar errores si alguna zona no existe en la máscara
        if not np.any(indices_figura):
            media_figura = [0.0, 0.0, 0.0]
        else:
            media_figura = [
                np.mean(r[indices_figura]),
                np.mean(g[indices_figura]),
                np.mean(b[indices_figura])
            ]

        if not np.any(indices_fondo):
            media_fondo = [0.0, 0.0, 0.0]
        else:
            media_fondo = [
                np.mean(r[indices_fondo]),
                np.mean(g[indices_fondo]),
                np.mean(b[indices_fondo])
            ]

        caracteristicas_figura.append(media_figura)
        caracteristicas_fondo.append(media_fondo)

    return (
        np.array(caracteristicas_figura, dtype=np.float32),
        np.array(caracteristicas_fondo, dtype=np.float32)
    )

Extraemos el contorno de los animales

from skimage.measure import label, regionprops
import numpy as np

def extraer_ratio_area_contorno(mascaras_binarias):
    ratios = []

    for mascara in mascaras_binarias:
        # Etiquetar regiones conectadas
        etiqueta = label(mascara)

        # Extraer propiedades
        regiones = regionprops(etiqueta)

        if len(regiones) > 0:
            # Tomamos la región de mayor área
            region_principal = max(regiones, key=lambda r: r.area)

            area_real = region_principal.area
            minr, minc, maxr, maxc = region_principal.bbox
            alto = maxr - minr
            ancho = maxc - minc
            area_rect = alto * ancho

            proporcion = area_real / area_rect if area_rect > 0 else 0.0
            ratios.append(proporcion)
        else:
            ratios.append(0.0)

    return np.array(ratios, dtype=np.float32).reshape(-1, 1)

Extraemos texturas mediante orientación de gradiente

from scipy.ndimage import gaussian_filter   
from skimage import color                   
import numpy as np                          

def generar_mapa_direcciones(angulo_grad, num_direcciones):
    # Calcula el ancho (en grados) de cada sector angular
    paso = 360 / num_direcciones

    # Define los centros de cada sector en el rango [-180, 180]
    sectores = np.linspace(-180, 180, num_direcciones)

    # Inicializa un mapa 3D (alto x ancho x num_direcciones) con ceros
    mapa_direcciones = np.zeros((*angulo_grad.shape, num_direcciones), dtype=int)

    # Para cada sector direccional, marca los píxeles que caen dentro del ángulo
    for idx, centro in enumerate(sectores):
        # Crea una máscara binaria donde el ángulo está dentro del sector
        dentro_sector = np.abs(angulo_grad - centro) < paso / 2

        # Almacena esa máscara en la capa correspondiente del mapa
        mapa_direcciones[:, :, idx] = dentro_sector.astype(int)

    # Devuelve el mapa direccional codificado como capas binarias
    return mapa_direcciones

def extraer_caracteristicas_textura(imagenes, mascaras):
    textura_total = []             # Lista para almacenar histogramas de cada imagen
    suavizado_sigma = 1           # Valor sigma para el filtro gaussiano

    # Itera sobre todas las imágenes y sus respectivas máscaras
    for img, mask in zip(imagenes, mascaras):
        # Convierte la imagen a escala de grises para análisis de gradiente
        img_gray = color.rgb2gray(img)

        # Aplica un suavizado Gaussiano para reducir el ruido antes del gradiente
        suavizada = gaussian_filter(img_gray, sigma=suavizado_sigma)

        # Calcula el gradiente en x (horizontal) y en y (vertical)
        grad_x = np.gradient(suavizada, axis=1)
        grad_y = np.gradient(suavizada, axis=0)

        # Calcula el ángulo de orientación del gradiente en grados
        orientacion = np.arctan2(grad_y, grad_x) * (180 / np.pi)

        # Convierte los ángulos en un mapa de direcciones discretas
        mapa = generar_mapa_direcciones(orientacion, 8)

        # Aplica la máscara binaria a cada canal direccional (solo figura)
        direcciones_validas = mapa * mask[:, :, np.newaxis]

        # Suma los valores válidos por canal direccional → histograma 1D de 8 valores
        histograma = np.sum(direcciones_validas, axis=(0, 1))

        # Normaliza el histograma para que represente proporciones
        histograma_norm = histograma / np.sum(histograma)

        # Almacena el histograma normalizado como características de textura
        textura_total.append(histograma_norm)

    # Devuelve una matriz (n_imágenes x 8) con los histogramas de textura
    return np.array(textura_total)

import numpy as np

# Extracción de características usando las imágenes aumentadas
caracteristicas_figura, caracteristicas_fondo = obtener_medias_rgb(imagenes_aug, mascaras_aug)
caracteristicas_contorno1 = extraer_ratio_area_contorno(mascaras_aug)
caracteristicas_textura = extraer_caracteristicas_textura(imagenes_aug, mascaras_aug)

# Construcción del conjunto de características y etiquetas
X = np.hstack([
    caracteristicas_figura,
    caracteristicas_fondo,
    caracteristicas_contorno1,
    caracteristicas_textura
])
y = etiquetas_aug
imgs = imagenes_aug
masks = mascaras_aug

# Verificación de dimensiones
print(" Dimensiones de las características:")
print(f"  RGB figura: {caracteristicas_figura.shape}")
print(f"  RGB fondo: {caracteristicas_fondo.shape}")
print(f"  Contorno (área): {caracteristicas_contorno1.shape}")
print(f"  Texturas direccionales: {caracteristicas_textura.shape}")
print(f"  Conjunto unificado: {X.shape}")

 Dimensiones de las características:
  RGB figura: (729, 3)
  RGB fondo: (729, 3)
  Contorno (área): (729, 1)
  Texturas direccionales: (729, 8)
  Conjunto unificado: (729, 15)

import matplotlib.pyplot as plt
from skimage import color
from skimage.measure import label, regionprops, moments, moments_hu
from scipy.ndimage import gaussian_filter
import numpy as np

def visualizar_caracteristicas(imagen, mascara, mostrar_texto=True):
    fig, axs = plt.subplots(2, 3, figsize=(15, 10))
    axs = axs.ravel()
    
    # Imagen original
    axs[0].imshow(imagen)
    axs[0].set_title("Imagen original")
    axs[0].axis('off')
    
    # Máscara binaria (figura)
    axs[1].imshow(mascara, cmap='gray')
    axs[1].set_title("Máscara (figura)")
    axs[1].axis('off')
    
    # Fondo enmascarado
    fondo = imagen.copy()
    fondo[mascara == 1] = 0
    axs[2].imshow(fondo)
    axs[2].set_title("Fondo (imagen sin figura)")
    axs[2].axis('off')

    # Ángulo del gradiente
    imagen_gris = color.rgb2gray(imagen)
    suavizada = gaussian_filter(imagen_gris, sigma=1)
    dx = np.gradient(suavizada, axis=1)
    dy = np.gradient(suavizada, axis=0)
    angulo = np.arctan2(dy, dx) * (180 / np.pi)
    axs[3].imshow(angulo, cmap='twilight', vmin=-180, vmax=180)
    axs[3].set_title("Ángulo del gradiente")
    axs[3].axis('off')
    
    # Histograma de direcciones
    direcciones = generar_mapa_direcciones(angulo, 8)
    direcciones_mascaradas = direcciones * mascara[:, :, np.newaxis]
    frecuencias = np.sum(direcciones_mascaradas, axis=(0, 1))
    axs[4].bar(range(8), frecuencias)
    axs[4].set_title("Histograma de direcciones")
    axs[4].set_xlabel("Sector")
    axs[4].set_ylabel("Frecuencia")

    # Datos numéricos
    if mostrar_texto:
        # Medias RGB figura
        rgb_figura = imagen[mascara == 1]
        media_rgb = np.mean(rgb_figura, axis=0)

        # Momentos de Hu con skimage
        etiqueta = label(mascara)
        regiones = regionprops(etiqueta)

        texto = "Medias RGB figura:\n" + \
                f"R: {media_rgb[0]:.2f}  G: {media_rgb[1]:.2f}  B: {media_rgb[2]:.2f}\n\n"


        axs[5].axis('off')
        axs[5].text(0.01, 0.95, texto, fontsize=10, verticalalignment='top')
    else:
        axs[5].axis('off')
    
    plt.tight_layout()
    plt.show()

# Ejemplo de uso
visualizar_caracteristicas(imagenes[0], mascaras[0])

Definimos el modelo y entrenamos con todas las característicaas extraídas

Dividimos los datos en entrenamiento y test

from sklearn.model_selection import train_test_split

# División del dataset en entrenamiento y prueba
X_train, X_test, y_train, y_test, imgs_train, imgs_test, masks_train, masks_test = train_test_split(
    X, y, imgs, masks, test_size=0.2, random_state=42, stratify=y
)

# Información sobre la división
print("\nDivisión del dataset:")
print("────────────────────────────")
print("Conjunto de entrenamiento:")
print(f"  X_train: {X_train.shape}")
print(f"  y_train: {y_train.shape}")
print(f"  imgs_train: {imgs_train.shape}")
print(f"  masks_train: {masks_train.shape}")

print("\nConjunto de prueba:")
print(f"  X_test: {X_test.shape}")
print(f"  y_test: {y_test.shape}")
print(f"  imgs_test: {imgs_test.shape}")
print(f"  masks_test: {masks_test.shape}")

División del dataset:
────────────────────────────
Conjunto de entrenamiento:
  X_train: (583, 15)
  y_train: (583,)
  imgs_train: (583, 200, 300, 3)
  masks_train: (583, 200, 300)

Conjunto de prueba:
  X_test: (146, 15)
  y_test: (146,)
  imgs_test: (146, 200, 300, 3)
  masks_test: (146, 200, 300)

Vamos a probar distintas combinaciones de hiperparámetros para ver cuáles son mejores para nuestro entrenamiento

Se comparan mediante el f1-score ya que busca equilibrio entre precision y recall, solo será alto si ambos son altos.

from sklearn.preprocessing import StandardScaler
from tensorflow.keras.utils import to_categorical

# Reemplazar valores no finitos por ceros
X_train = np.nan_to_num(X_train, nan=0.0, posinf=0.0, neginf=0.0)
X_test = np.nan_to_num(X_test, nan=0.0, posinf=0.0, neginf=0.0)

# Escalado estándar de los datos de entrada
normalizer = StandardScaler()
X_train_scaled = normalizer.fit_transform(X_train)
X_test_scaled = normalizer.transform(X_test)

# Conversión explícita de etiquetas a enteros y luego a one-hot encoding (float32)
y_train = y_train.astype("int32")
y_test = y_test.astype("int32")

Y_train_onehot = to_categorical(y_train, num_classes=3).astype("float32")
Y_test_onehot = to_categorical(y_test, num_classes=3).astype("float32")

# Definición de los hiperparámetros a probar
lr_options = [0.001, 0.01, 0.1]
dropout_values = [0.4, 0.6, 0.8]
batch_options = [4, 8, 16]

from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score
from keras.models import Sequential
from keras.layers import Dense, Dropout, Input, BatchNormalization
from keras.optimizers import Adam

# Número de clases de salida (según el one-hot encoding)
n_classes = Y_train_onehot.shape[1]

# Lista para almacenar los resultados de evaluación del modelo
eval_metrics = []

# Bucle de búsqueda de hiperparámetros
for lr in lr_options:
    for drop in dropout_values:
        for batch in batch_options:

            # Definición de la arquitectura de la red neuronal
            network = Sequential([
                Input(shape=(X_train_scaled.shape[1],)),
                Dense(256, activation='relu'),
                BatchNormalization(),
                Dropout(drop),

                Dense(128, activation='tanh'),
                Dropout(drop),

                Dense(64, activation='relu'),
                Dropout(drop),

                Dense(32, activation='relu'),
                Dropout(drop),

                Dense(16, activation='relu'),
                Dense(n_classes, activation='softmax')  # Capa de salida con softmax para clasificación multiclase
            ])

            # Compilación del modelo
            network.compile(
                optimizer=Adam(learning_rate=lr),
                loss='categorical_crossentropy',
                metrics=['accuracy', 'Precision', 'Recall', 'AUC']
            )

            # Entrenamiento del modelo 
            network.fit(X_train_scaled, Y_train_onehot, epochs=50, batch_size=batch, verbose=1)

            # Predicción sobre el conjunto de test
            preds = network.predict(X_test_scaled)
            pred_labels = np.argmax(preds, axis=1)
            true_labels = np.argmax(Y_test_onehot, axis=1)

            # Cálculo de las métricas de evaluación
            acc = accuracy_score(true_labels, pred_labels)
            prec = precision_score(true_labels, pred_labels, average='macro', zero_division=0.0)
            rec = recall_score(true_labels, pred_labels, average='macro', zero_division=0.0)
            f1 = f1_score(true_labels, pred_labels, average='macro', zero_division=0.0)

            # Almacenamiento de las métricas junto con los hiperparámetros usados
            eval_metrics.append({
                'learning_rate': lr,
                'dropout_rate': drop,
                'batch_size': batch,
                'accuracy': acc,
                'precision': prec,
                'recall': rec,
                'f1': f1
            })

# Selección de la mejor configuración según el F1-score
optimal_config = max(eval_metrics, key=lambda res: res['f1'])

print("Mejor combinación de hiperparámetros:")
print(optimal_config)

Epoch 1/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 9s 6ms/step - AUC: 0.5121 - Precision: 0.3715 - Recall: 0.1919 - accuracy: 0.3538 - loss: 1.2963
Epoch 2/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6900 - Precision: 0.6262 - Recall: 0.3423 - accuracy: 0.4889 - loss: 1.0122
Epoch 3/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7756 - Precision: 0.7009 - Recall: 0.4040 - accuracy: 0.5893 - loss: 0.9036
Epoch 4/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7935 - Precision: 0.7043 - Recall: 0.4510 - accuracy: 0.6052 - loss: 0.8381
Epoch 5/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7893 - Precision: 0.6839 - Recall: 0.4344 - accuracy: 0.5984 - loss: 0.8475
Epoch 6/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8055 - Precision: 0.7031 - Recall: 0.4407 - accuracy: 0.6147 - loss: 0.8395
Epoch 7/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8088 - Precision: 0.6982 - Recall: 0.4565 - accuracy: 0.5962 - loss: 0.7999
Epoch 8/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8393 - Precision: 0.7609 - Recall: 0.5030 - accuracy: 0.6233 - loss: 0.7480
Epoch 9/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8131 - Precision: 0.6982 - Recall: 0.4632 - accuracy: 0.6176 - loss: 0.8385
Epoch 10/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8260 - Precision: 0.7712 - Recall: 0.4851 - accuracy: 0.6268 - loss: 0.7765
Epoch 11/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8273 - Precision: 0.7209 - Recall: 0.4838 - accuracy: 0.6026 - loss: 0.7666
Epoch 12/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8458 - Precision: 0.7447 - Recall: 0.5010 - accuracy: 0.6499 - loss: 0.7495
Epoch 13/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8338 - Precision: 0.7884 - Recall: 0.4881 - accuracy: 0.6368 - loss: 0.7776
Epoch 14/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8166 - Precision: 0.6907 - Recall: 0.4576 - accuracy: 0.6020 - loss: 0.8034
Epoch 15/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8266 - Precision: 0.7666 - Recall: 0.4693 - accuracy: 0.6124 - loss: 0.7656
Epoch 16/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8427 - Precision: 0.7571 - Recall: 0.4793 - accuracy: 0.6419 - loss: 0.7315
Epoch 17/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8394 - Precision: 0.7568 - Recall: 0.4893 - accuracy: 0.6109 - loss: 0.7260
Epoch 18/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8626 - Precision: 0.7782 - Recall: 0.5038 - accuracy: 0.6639 - loss: 0.6845
Epoch 19/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8510 - Precision: 0.7395 - Recall: 0.5045 - accuracy: 0.6428 - loss: 0.7286
Epoch 20/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8567 - Precision: 0.7797 - Recall: 0.4779 - accuracy: 0.6145 - loss: 0.6823
Epoch 21/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8510 - Precision: 0.7536 - Recall: 0.4871 - accuracy: 0.6120 - loss: 0.7216
Epoch 22/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8400 - Precision: 0.7252 - Recall: 0.4631 - accuracy: 0.6177 - loss: 0.7426
Epoch 23/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8530 - Precision: 0.7528 - Recall: 0.4674 - accuracy: 0.6604 - loss: 0.7004
Epoch 24/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8552 - Precision: 0.8036 - Recall: 0.4888 - accuracy: 0.6433 - loss: 0.7016
Epoch 25/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8509 - Precision: 0.7448 - Recall: 0.5486 - accuracy: 0.6385 - loss: 0.7524
Epoch 26/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8641 - Precision: 0.7498 - Recall: 0.4894 - accuracy: 0.6669 - loss: 0.6942
Epoch 27/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8396 - Precision: 0.7518 - Recall: 0.4992 - accuracy: 0.6352 - loss: 0.7509
Epoch 28/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8595 - Precision: 0.7055 - Recall: 0.5045 - accuracy: 0.6429 - loss: 0.7259
Epoch 29/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8615 - Precision: 0.7577 - Recall: 0.5221 - accuracy: 0.6608 - loss: 0.7114
Epoch 30/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8505 - Precision: 0.7689 - Recall: 0.5026 - accuracy: 0.6611 - loss: 0.7240
Epoch 31/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8810 - Precision: 0.7836 - Recall: 0.5742 - accuracy: 0.6810 - loss: 0.6373
Epoch 32/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8862 - Precision: 0.7932 - Recall: 0.5529 - accuracy: 0.7070 - loss: 0.6444
Epoch 33/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8719 - Precision: 0.7953 - Recall: 0.5444 - accuracy: 0.6743 - loss: 0.6593
Epoch 34/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8898 - Precision: 0.8055 - Recall: 0.5991 - accuracy: 0.7061 - loss: 0.6380
Epoch 35/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8859 - Precision: 0.7794 - Recall: 0.5878 - accuracy: 0.7085 - loss: 0.6332
Epoch 36/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8642 - Precision: 0.7251 - Recall: 0.5004 - accuracy: 0.6232 - loss: 0.6611
Epoch 37/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8849 - Precision: 0.7453 - Recall: 0.5529 - accuracy: 0.6861 - loss: 0.6163
Epoch 38/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8846 - Precision: 0.8032 - Recall: 0.5642 - accuracy: 0.6576 - loss: 0.6192
Epoch 39/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.8580 - Precision: 0.7444 - Recall: 0.5380 - accuracy: 0.6589 - loss: 0.7297
Epoch 40/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.8552 - Precision: 0.7181 - Recall: 0.4969 - accuracy: 0.6496 - loss: 0.7259
Epoch 41/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8777 - Precision: 0.7453 - Recall: 0.5581 - accuracy: 0.6840 - loss: 0.6449
Epoch 42/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8818 - Precision: 0.7605 - Recall: 0.5871 - accuracy: 0.7014 - loss: 0.6323
Epoch 43/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.8956 - Precision: 0.7865 - Recall: 0.6003 - accuracy: 0.7135 - loss: 0.6022
Epoch 44/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.9087 - Precision: 0.7993 - Recall: 0.6172 - accuracy: 0.7459 - loss: 0.5780
Epoch 45/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8661 - Precision: 0.7559 - Recall: 0.5881 - accuracy: 0.6926 - loss: 0.6832
Epoch 46/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8809 - Precision: 0.7669 - Recall: 0.5760 - accuracy: 0.7148 - loss: 0.6467
Epoch 47/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8462 - Precision: 0.7347 - Recall: 0.5227 - accuracy: 0.6275 - loss: 0.7322
Epoch 48/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8861 - Precision: 0.7896 - Recall: 0.5407 - accuracy: 0.6884 - loss: 0.6267
Epoch 49/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8811 - Precision: 0.7848 - Recall: 0.5299 - accuracy: 0.6875 - loss: 0.6527
Epoch 50/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8632 - Precision: 0.7376 - Recall: 0.5449 - accuracy: 0.6401 - loss: 0.6841
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 35ms/step
Epoch 1/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 4s 4ms/step - AUC: 0.4733 - Precision: 0.3092 - Recall: 0.1456 - accuracy: 0.3102 - loss: 1.3131
Epoch 2/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7447 - Precision: 0.6725 - Recall: 0.3489 - accuracy: 0.5820 - loss: 0.9345
Epoch 3/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7655 - Precision: 0.7384 - Recall: 0.4145 - accuracy: 0.5632 - loss: 0.8679
Epoch 4/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7782 - Precision: 0.6927 - Recall: 0.3773 - accuracy: 0.5736 - loss: 0.8620
Epoch 5/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8297 - Precision: 0.7269 - Recall: 0.4611 - accuracy: 0.6156 - loss: 0.7694
Epoch 6/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8543 - Precision: 0.7576 - Recall: 0.4954 - accuracy: 0.6593 - loss: 0.7249
Epoch 7/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8716 - Precision: 0.8009 - Recall: 0.5399 - accuracy: 0.6782 - loss: 0.6725
Epoch 8/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8384 - Precision: 0.7318 - Recall: 0.4350 - accuracy: 0.6299 - loss: 0.7565
Epoch 9/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8628 - Precision: 0.8205 - Recall: 0.5452 - accuracy: 0.6711 - loss: 0.7329
Epoch 10/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8710 - Precision: 0.7900 - Recall: 0.4978 - accuracy: 0.6279 - loss: 0.6594
Epoch 11/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.8779 - Precision: 0.7771 - Recall: 0.5511 - accuracy: 0.6986 - loss: 0.6712
Epoch 12/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8773 - Precision: 0.8026 - Recall: 0.5284 - accuracy: 0.7076 - loss: 0.6564
Epoch 13/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8633 - Precision: 0.7502 - Recall: 0.4951 - accuracy: 0.6648 - loss: 0.6729
Epoch 14/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8762 - Precision: 0.7894 - Recall: 0.5340 - accuracy: 0.6824 - loss: 0.6756
Epoch 15/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8751 - Precision: 0.7396 - Recall: 0.5382 - accuracy: 0.6596 - loss: 0.6306
Epoch 16/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8818 - Precision: 0.7689 - Recall: 0.5613 - accuracy: 0.7003 - loss: 0.6343
Epoch 17/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8891 - Precision: 0.7615 - Recall: 0.5764 - accuracy: 0.6860 - loss: 0.5933
Epoch 18/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8723 - Precision: 0.7257 - Recall: 0.5410 - accuracy: 0.6424 - loss: 0.6255
Epoch 19/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8890 - Precision: 0.8146 - Recall: 0.5804 - accuracy: 0.6890 - loss: 0.6301
Epoch 20/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8893 - Precision: 0.7792 - Recall: 0.5847 - accuracy: 0.7076 - loss: 0.6244
Epoch 21/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8937 - Precision: 0.7666 - Recall: 0.5721 - accuracy: 0.6863 - loss: 0.5848
Epoch 22/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8984 - Precision: 0.7756 - Recall: 0.5984 - accuracy: 0.6947 - loss: 0.5847
Epoch 23/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8868 - Precision: 0.7676 - Recall: 0.5615 - accuracy: 0.6857 - loss: 0.6201
Epoch 24/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8718 - Precision: 0.7273 - Recall: 0.5453 - accuracy: 0.6443 - loss: 0.6382
Epoch 25/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8791 - Precision: 0.7786 - Recall: 0.5398 - accuracy: 0.6653 - loss: 0.6435
Epoch 26/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8961 - Precision: 0.7720 - Recall: 0.5864 - accuracy: 0.6820 - loss: 0.5786
Epoch 27/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8882 - Precision: 0.7941 - Recall: 0.5795 - accuracy: 0.7069 - loss: 0.6312
Epoch 28/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8964 - Precision: 0.7936 - Recall: 0.5930 - accuracy: 0.6963 - loss: 0.5750
Epoch 29/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.9208 - Precision: 0.8017 - Recall: 0.6312 - accuracy: 0.7427 - loss: 0.5052
Epoch 30/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.9041 - Precision: 0.7718 - Recall: 0.6010 - accuracy: 0.7143 - loss: 0.5600
Epoch 31/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9026 - Precision: 0.7760 - Recall: 0.6162 - accuracy: 0.6960 - loss: 0.5602
Epoch 32/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.9147 - Precision: 0.8089 - Recall: 0.5939 - accuracy: 0.7353 - loss: 0.5333
Epoch 33/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.9007 - Precision: 0.7637 - Recall: 0.6140 - accuracy: 0.6990 - loss: 0.5581
Epoch 34/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.9186 - Precision: 0.8070 - Recall: 0.6693 - accuracy: 0.7441 - loss: 0.5277
Epoch 35/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8928 - Precision: 0.7278 - Recall: 0.5837 - accuracy: 0.6802 - loss: 0.5990
Epoch 36/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8849 - Precision: 0.7537 - Recall: 0.5883 - accuracy: 0.6737 - loss: 0.6249
Epoch 37/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8963 - Precision: 0.7438 - Recall: 0.5505 - accuracy: 0.6850 - loss: 0.5682
Epoch 38/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.9056 - Precision: 0.7683 - Recall: 0.5853 - accuracy: 0.7125 - loss: 0.5546
Epoch 39/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9285 - Precision: 0.8380 - Recall: 0.6754 - accuracy: 0.7689 - loss: 0.4904
Epoch 40/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8843 - Precision: 0.7022 - Recall: 0.5707 - accuracy: 0.6493 - loss: 0.6114
Epoch 41/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.9085 - Precision: 0.7538 - Recall: 0.6165 - accuracy: 0.7230 - loss: 0.5299
Epoch 42/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9325 - Precision: 0.8397 - Recall: 0.6908 - accuracy: 0.7979 - loss: 0.4901
Epoch 43/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8893 - Precision: 0.7400 - Recall: 0.5992 - accuracy: 0.6915 - loss: 0.6150
Epoch 44/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.9216 - Precision: 0.7764 - Recall: 0.6862 - accuracy: 0.7517 - loss: 0.5181
Epoch 45/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9180 - Precision: 0.7826 - Recall: 0.6699 - accuracy: 0.7494 - loss: 0.5179
Epoch 46/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9140 - Precision: 0.7878 - Recall: 0.6412 - accuracy: 0.7231 - loss: 0.5336
Epoch 47/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9130 - Precision: 0.7673 - Recall: 0.6621 - accuracy: 0.7158 - loss: 0.5353
Epoch 48/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.9177 - Precision: 0.7833 - Recall: 0.6269 - accuracy: 0.7308 - loss: 0.5305
Epoch 49/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9217 - Precision: 0.8000 - Recall: 0.6821 - accuracy: 0.7526 - loss: 0.5200
Epoch 50/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9240 - Precision: 0.7712 - Recall: 0.6685 - accuracy: 0.7334 - loss: 0.4835
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 60ms/step
Epoch 1/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 4s 5ms/step - AUC: 0.5042 - Precision: 0.3257 - Recall: 0.2110 - accuracy: 0.3269 - loss: 1.3456
Epoch 2/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7058 - Precision: 0.6238 - Recall: 0.3769 - accuracy: 0.5109 - loss: 0.9954
Epoch 3/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7527 - Precision: 0.7180 - Recall: 0.4008 - accuracy: 0.5495 - loss: 0.9285
Epoch 4/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8034 - Precision: 0.7112 - Recall: 0.4592 - accuracy: 0.5932 - loss: 0.8158
Epoch 5/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8206 - Precision: 0.7412 - Recall: 0.5103 - accuracy: 0.6055 - loss: 0.7740
Epoch 6/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8404 - Precision: 0.7600 - Recall: 0.5005 - accuracy: 0.6227 - loss: 0.7605
Epoch 7/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8470 - Precision: 0.7277 - Recall: 0.5222 - accuracy: 0.6555 - loss: 0.7228
Epoch 8/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8551 - Precision: 0.7250 - Recall: 0.5266 - accuracy: 0.6543 - loss: 0.7026
Epoch 9/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8652 - Precision: 0.7540 - Recall: 0.5242 - accuracy: 0.6535 - loss: 0.6755
Epoch 10/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8713 - Precision: 0.7699 - Recall: 0.5440 - accuracy: 0.6651 - loss: 0.6448
Epoch 11/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8772 - Precision: 0.7824 - Recall: 0.5846 - accuracy: 0.6770 - loss: 0.6638
Epoch 12/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8939 - Precision: 0.7544 - Recall: 0.5869 - accuracy: 0.6893 - loss: 0.5833
Epoch 13/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8967 - Precision: 0.7898 - Recall: 0.5979 - accuracy: 0.7318 - loss: 0.5973
Epoch 14/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8849 - Precision: 0.7425 - Recall: 0.5880 - accuracy: 0.6770 - loss: 0.6121
Epoch 15/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8832 - Precision: 0.7611 - Recall: 0.5696 - accuracy: 0.6689 - loss: 0.6198
Epoch 16/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8840 - Precision: 0.7541 - Recall: 0.5779 - accuracy: 0.6823 - loss: 0.6225
Epoch 17/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9111 - Precision: 0.7783 - Recall: 0.6457 - accuracy: 0.7336 - loss: 0.5477
Epoch 18/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8909 - Precision: 0.7428 - Recall: 0.6076 - accuracy: 0.6828 - loss: 0.5976
Epoch 19/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8984 - Precision: 0.8082 - Recall: 0.5927 - accuracy: 0.7148 - loss: 0.5879
Epoch 20/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9046 - Precision: 0.7611 - Recall: 0.6120 - accuracy: 0.7125 - loss: 0.5689
Epoch 21/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8943 - Precision: 0.7585 - Recall: 0.6044 - accuracy: 0.6754 - loss: 0.5856
Epoch 22/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8961 - Precision: 0.7621 - Recall: 0.6071 - accuracy: 0.7020 - loss: 0.5740
Epoch 23/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9107 - Precision: 0.7675 - Recall: 0.6368 - accuracy: 0.7200 - loss: 0.5491
Epoch 24/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9117 - Precision: 0.7892 - Recall: 0.6417 - accuracy: 0.7224 - loss: 0.5318
Epoch 25/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9161 - Precision: 0.7951 - Recall: 0.6624 - accuracy: 0.7320 - loss: 0.5351
Epoch 26/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9127 - Precision: 0.7905 - Recall: 0.6662 - accuracy: 0.7177 - loss: 0.5450
Epoch 27/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9236 - Precision: 0.8058 - Recall: 0.7005 - accuracy: 0.7466 - loss: 0.4929
Epoch 28/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8935 - Precision: 0.7476 - Recall: 0.5922 - accuracy: 0.6707 - loss: 0.5865
Epoch 29/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9164 - Precision: 0.7987 - Recall: 0.6662 - accuracy: 0.7245 - loss: 0.5236
Epoch 30/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9231 - Precision: 0.8041 - Recall: 0.6599 - accuracy: 0.7583 - loss: 0.5401
Epoch 31/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9208 - Precision: 0.8078 - Recall: 0.6557 - accuracy: 0.7537 - loss: 0.5394
Epoch 32/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.9217 - Precision: 0.8097 - Recall: 0.6650 - accuracy: 0.7420 - loss: 0.5155
Epoch 33/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9215 - Precision: 0.8190 - Recall: 0.6328 - accuracy: 0.7360 - loss: 0.5170
Epoch 34/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9202 - Precision: 0.7853 - Recall: 0.6424 - accuracy: 0.7369 - loss: 0.5227
Epoch 35/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9254 - Precision: 0.7682 - Recall: 0.6549 - accuracy: 0.7412 - loss: 0.4795
Epoch 36/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9264 - Precision: 0.8050 - Recall: 0.6839 - accuracy: 0.7532 - loss: 0.4853
Epoch 37/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9174 - Precision: 0.7873 - Recall: 0.6308 - accuracy: 0.7405 - loss: 0.5248
Epoch 38/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9136 - Precision: 0.8023 - Recall: 0.6544 - accuracy: 0.7257 - loss: 0.5455
Epoch 39/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9240 - Precision: 0.8026 - Recall: 0.7093 - accuracy: 0.7472 - loss: 0.5153
Epoch 40/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9311 - Precision: 0.8192 - Recall: 0.7266 - accuracy: 0.7844 - loss: 0.4952
Epoch 41/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9143 - Precision: 0.7605 - Recall: 0.6728 - accuracy: 0.7111 - loss: 0.5399
Epoch 42/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9372 - Precision: 0.8207 - Recall: 0.7142 - accuracy: 0.7800 - loss: 0.4646
Epoch 43/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8934 - Precision: 0.7618 - Recall: 0.6718 - accuracy: 0.7185 - loss: 0.6255
Epoch 44/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9288 - Precision: 0.7988 - Recall: 0.6798 - accuracy: 0.7541 - loss: 0.4790
Epoch 45/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9314 - Precision: 0.8274 - Recall: 0.7017 - accuracy: 0.7581 - loss: 0.4770
Epoch 46/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.9319 - Precision: 0.8143 - Recall: 0.7238 - accuracy: 0.7622 - loss: 0.4847
Epoch 47/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9409 - Precision: 0.8277 - Recall: 0.7318 - accuracy: 0.7998 - loss: 0.4429
Epoch 48/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9409 - Precision: 0.8384 - Recall: 0.7525 - accuracy: 0.7968 - loss: 0.4689
Epoch 49/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9291 - Precision: 0.8014 - Recall: 0.7039 - accuracy: 0.7604 - loss: 0.4856
Epoch 50/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9234 - Precision: 0.8060 - Recall: 0.6819 - accuracy: 0.7588 - loss: 0.5142
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step
Epoch 1/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 5s 4ms/step - AUC: 0.6170 - Precision: 0.4674 - Recall: 0.3408 - accuracy: 0.4409 - loss: 1.3235
Epoch 2/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.6264 - Precision: 0.5273 - Recall: 0.2886 - accuracy: 0.4949 - loss: 1.1669
Epoch 3/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6730 - Precision: 0.5537 - Recall: 0.2998 - accuracy: 0.4880 - loss: 1.0229
Epoch 4/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.6626 - Precision: 0.6291 - Recall: 0.3022 - accuracy: 0.4823 - loss: 1.0432
Epoch 5/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7151 - Precision: 0.6591 - Recall: 0.3164 - accuracy: 0.5441 - loss: 0.9796
Epoch 6/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7461 - Precision: 0.7501 - Recall: 0.3412 - accuracy: 0.5554 - loss: 0.9409
Epoch 7/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7585 - Precision: 0.7780 - Recall: 0.3574 - accuracy: 0.5787 - loss: 0.8831
Epoch 8/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7947 - Precision: 0.7461 - Recall: 0.3994 - accuracy: 0.5784 - loss: 0.8354
Epoch 9/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.7584 - Precision: 0.7797 - Recall: 0.3586 - accuracy: 0.5548 - loss: 0.8937
Epoch 10/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7930 - Precision: 0.7907 - Recall: 0.3749 - accuracy: 0.5892 - loss: 0.8213
Epoch 11/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.7982 - Precision: 0.7711 - Recall: 0.3871 - accuracy: 0.6018 - loss: 0.8160
Epoch 12/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8190 - Precision: 0.7922 - Recall: 0.4147 - accuracy: 0.6376 - loss: 0.8235
Epoch 13/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.7951 - Precision: 0.7938 - Recall: 0.3507 - accuracy: 0.5876 - loss: 0.8460
Epoch 14/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8317 - Precision: 0.8331 - Recall: 0.4138 - accuracy: 0.6456 - loss: 0.7565
Epoch 15/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8135 - Precision: 0.7762 - Recall: 0.4133 - accuracy: 0.6123 - loss: 0.8089
Epoch 16/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8049 - Precision: 0.7820 - Recall: 0.3917 - accuracy: 0.5878 - loss: 0.8056
Epoch 17/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.8234 - Precision: 0.7931 - Recall: 0.4217 - accuracy: 0.5933 - loss: 0.7896
Epoch 18/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.7718 - Precision: 0.7358 - Recall: 0.3711 - accuracy: 0.5814 - loss: 0.8892
Epoch 19/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8260 - Precision: 0.7751 - Recall: 0.4125 - accuracy: 0.6222 - loss: 0.7575
Epoch 20/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8237 - Precision: 0.8422 - Recall: 0.4191 - accuracy: 0.6167 - loss: 0.7817
Epoch 21/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8386 - Precision: 0.8323 - Recall: 0.4192 - accuracy: 0.6051 - loss: 0.7875
Epoch 22/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8376 - Precision: 0.8051 - Recall: 0.4434 - accuracy: 0.6297 - loss: 0.7528
Epoch 23/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8295 - Precision: 0.7829 - Recall: 0.4342 - accuracy: 0.5979 - loss: 0.7534
Epoch 24/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8195 - Precision: 0.7677 - Recall: 0.3810 - accuracy: 0.6175 - loss: 0.8043
Epoch 25/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8160 - Precision: 0.7671 - Recall: 0.3861 - accuracy: 0.6154 - loss: 0.8057
Epoch 26/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8209 - Precision: 0.7796 - Recall: 0.3999 - accuracy: 0.6432 - loss: 0.7834
Epoch 27/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8087 - Precision: 0.7773 - Recall: 0.3867 - accuracy: 0.5892 - loss: 0.8162
Epoch 28/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8223 - Precision: 0.8126 - Recall: 0.3973 - accuracy: 0.6187 - loss: 0.8023
Epoch 29/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8376 - Precision: 0.7900 - Recall: 0.4106 - accuracy: 0.6372 - loss: 0.7496
Epoch 30/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8597 - Precision: 0.8599 - Recall: 0.4406 - accuracy: 0.6329 - loss: 0.6980
Epoch 31/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8342 - Precision: 0.8233 - Recall: 0.4478 - accuracy: 0.6084 - loss: 0.7588
Epoch 32/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8164 - Precision: 0.7630 - Recall: 0.3754 - accuracy: 0.5891 - loss: 0.7887
Epoch 33/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8432 - Precision: 0.7944 - Recall: 0.4440 - accuracy: 0.6260 - loss: 0.7441
Epoch 34/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8258 - Precision: 0.7531 - Recall: 0.4495 - accuracy: 0.6122 - loss: 0.7827
Epoch 35/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.8569 - Precision: 0.8303 - Recall: 0.4550 - accuracy: 0.6562 - loss: 0.7197
Epoch 36/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8143 - Precision: 0.7868 - Recall: 0.4061 - accuracy: 0.5769 - loss: 0.7931
Epoch 37/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.8424 - Precision: 0.7759 - Recall: 0.4485 - accuracy: 0.6224 - loss: 0.7275
Epoch 38/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.8329 - Precision: 0.7985 - Recall: 0.4443 - accuracy: 0.6196 - loss: 0.7668
Epoch 39/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8458 - Precision: 0.7668 - Recall: 0.4302 - accuracy: 0.6449 - loss: 0.7331
Epoch 40/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8561 - Precision: 0.8308 - Recall: 0.4805 - accuracy: 0.6566 - loss: 0.7176
Epoch 41/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8426 - Precision: 0.7665 - Recall: 0.4592 - accuracy: 0.6453 - loss: 0.7497
Epoch 42/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.8653 - Precision: 0.8253 - Recall: 0.4501 - accuracy: 0.6932 - loss: 0.7303
Epoch 43/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8178 - Precision: 0.7983 - Recall: 0.4009 - accuracy: 0.5939 - loss: 0.7917
Epoch 44/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8448 - Precision: 0.7896 - Recall: 0.4112 - accuracy: 0.6414 - loss: 0.7482
Epoch 45/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8246 - Precision: 0.8193 - Recall: 0.4061 - accuracy: 0.6365 - loss: 0.7774
Epoch 46/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8589 - Precision: 0.8659 - Recall: 0.4459 - accuracy: 0.6212 - loss: 0.7011
Epoch 47/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8408 - Precision: 0.8319 - Recall: 0.4459 - accuracy: 0.6305 - loss: 0.7629
Epoch 48/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8444 - Precision: 0.8311 - Recall: 0.4251 - accuracy: 0.6537 - loss: 0.7381
Epoch 49/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8298 - Precision: 0.7751 - Recall: 0.3971 - accuracy: 0.5928 - loss: 0.7847
Epoch 50/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.8703 - Precision: 0.8372 - Recall: 0.4793 - accuracy: 0.6762 - loss: 0.6742
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step
Epoch 1/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 4s 5ms/step - AUC: 0.4423 - Precision: 0.2933 - Recall: 0.2423 - accuracy: 0.2963 - loss: 2.1215
Epoch 2/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5391 - Precision: 0.3840 - Recall: 0.2421 - accuracy: 0.3732 - loss: 1.3337
Epoch 3/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5875 - Precision: 0.4356 - Recall: 0.2577 - accuracy: 0.4252 - loss: 1.2217
Epoch 4/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6106 - Precision: 0.4982 - Recall: 0.2673 - accuracy: 0.4144 - loss: 1.1273
Epoch 5/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.6555 - Precision: 0.6133 - Recall: 0.3257 - accuracy: 0.4695 - loss: 1.0761
Epoch 6/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6300 - Precision: 0.5103 - Recall: 0.2522 - accuracy: 0.4375 - loss: 1.0765
Epoch 7/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7182 - Precision: 0.6455 - Recall: 0.3350 - accuracy: 0.5169 - loss: 0.9831
Epoch 8/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.7234 - Precision: 0.6786 - Recall: 0.3612 - accuracy: 0.5258 - loss: 0.9360
Epoch 9/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7381 - Precision: 0.7239 - Recall: 0.3447 - accuracy: 0.5346 - loss: 0.9135
Epoch 10/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7525 - Precision: 0.7323 - Recall: 0.3645 - accuracy: 0.5471 - loss: 0.8868
Epoch 11/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7600 - Precision: 0.7420 - Recall: 0.3599 - accuracy: 0.5432 - loss: 0.8910
Epoch 12/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7580 - Precision: 0.7249 - Recall: 0.3845 - accuracy: 0.5602 - loss: 0.8739
Epoch 13/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8150 - Precision: 0.7927 - Recall: 0.4295 - accuracy: 0.6099 - loss: 0.8118
Epoch 14/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7873 - Precision: 0.7475 - Recall: 0.3950 - accuracy: 0.5645 - loss: 0.8399
Epoch 15/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8026 - Precision: 0.7289 - Recall: 0.3756 - accuracy: 0.5637 - loss: 0.8259
Epoch 16/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8136 - Precision: 0.7804 - Recall: 0.4106 - accuracy: 0.5851 - loss: 0.8079
Epoch 17/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8134 - Precision: 0.7442 - Recall: 0.4182 - accuracy: 0.5840 - loss: 0.8201
Epoch 18/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8264 - Precision: 0.7726 - Recall: 0.4397 - accuracy: 0.6102 - loss: 0.7869
Epoch 19/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8288 - Precision: 0.7287 - Recall: 0.4049 - accuracy: 0.6312 - loss: 0.7607
Epoch 20/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8455 - Precision: 0.7391 - Recall: 0.4261 - accuracy: 0.6323 - loss: 0.7304
Epoch 21/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8153 - Precision: 0.7428 - Recall: 0.4069 - accuracy: 0.6051 - loss: 0.7888
Epoch 22/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8450 - Precision: 0.7466 - Recall: 0.4686 - accuracy: 0.6423 - loss: 0.7118
Epoch 23/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8604 - Precision: 0.7983 - Recall: 0.5147 - accuracy: 0.6745 - loss: 0.7093
Epoch 24/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8434 - Precision: 0.7601 - Recall: 0.4587 - accuracy: 0.6442 - loss: 0.7421
Epoch 25/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8554 - Precision: 0.7960 - Recall: 0.4993 - accuracy: 0.6517 - loss: 0.7247
Epoch 26/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8644 - Precision: 0.7737 - Recall: 0.4894 - accuracy: 0.6435 - loss: 0.6851
Epoch 27/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8633 - Precision: 0.8124 - Recall: 0.4907 - accuracy: 0.6531 - loss: 0.6847
Epoch 28/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8740 - Precision: 0.7894 - Recall: 0.5026 - accuracy: 0.6907 - loss: 0.6847
Epoch 29/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8731 - Precision: 0.8150 - Recall: 0.4817 - accuracy: 0.6352 - loss: 0.6458
Epoch 30/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8569 - Precision: 0.7939 - Recall: 0.4903 - accuracy: 0.6439 - loss: 0.6975
Epoch 31/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8657 - Precision: 0.7652 - Recall: 0.4801 - accuracy: 0.6585 - loss: 0.6620
Epoch 32/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8684 - Precision: 0.7579 - Recall: 0.4938 - accuracy: 0.6588 - loss: 0.6595
Epoch 33/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8600 - Precision: 0.7996 - Recall: 0.5020 - accuracy: 0.6760 - loss: 0.7517
Epoch 34/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8437 - Precision: 0.7545 - Recall: 0.4910 - accuracy: 0.6244 - loss: 0.7884
Epoch 35/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8574 - Precision: 0.7768 - Recall: 0.4982 - accuracy: 0.6383 - loss: 0.7010
Epoch 36/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8751 - Precision: 0.7588 - Recall: 0.5175 - accuracy: 0.6617 - loss: 0.6398
Epoch 37/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8686 - Precision: 0.7625 - Recall: 0.5305 - accuracy: 0.6711 - loss: 0.6785
Epoch 38/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8663 - Precision: 0.7863 - Recall: 0.5219 - accuracy: 0.6594 - loss: 0.6843
Epoch 39/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8937 - Precision: 0.8586 - Recall: 0.5330 - accuracy: 0.6860 - loss: 0.5941
Epoch 40/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8685 - Precision: 0.7592 - Recall: 0.5105 - accuracy: 0.6496 - loss: 0.6728
Epoch 41/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8743 - Precision: 0.7804 - Recall: 0.4974 - accuracy: 0.6620 - loss: 0.6361
Epoch 42/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8723 - Precision: 0.8073 - Recall: 0.5430 - accuracy: 0.6867 - loss: 0.6802
Epoch 43/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8764 - Precision: 0.8068 - Recall: 0.5004 - accuracy: 0.6672 - loss: 0.6584
Epoch 44/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9007 - Precision: 0.8082 - Recall: 0.5550 - accuracy: 0.6902 - loss: 0.5961
Epoch 45/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8783 - Precision: 0.8100 - Recall: 0.5271 - accuracy: 0.6737 - loss: 0.6490
Epoch 46/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8613 - Precision: 0.7800 - Recall: 0.4997 - accuracy: 0.6495 - loss: 0.6982
Epoch 47/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8805 - Precision: 0.7965 - Recall: 0.5126 - accuracy: 0.6720 - loss: 0.6448
Epoch 48/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8851 - Precision: 0.8029 - Recall: 0.5266 - accuracy: 0.6691 - loss: 0.6078
Epoch 49/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8892 - Precision: 0.7884 - Recall: 0.5237 - accuracy: 0.6987 - loss: 0.6091
Epoch 50/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8596 - Precision: 0.7365 - Recall: 0.5130 - accuracy: 0.6447 - loss: 0.7022
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step
Epoch 1/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 4s 5ms/step - AUC: 0.4859 - Precision: 0.2868 - Recall: 0.1893 - accuracy: 0.3087 - loss: 1.4429
Epoch 2/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5943 - Precision: 0.4308 - Recall: 0.2108 - accuracy: 0.3989 - loss: 1.1731
Epoch 3/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6257 - Precision: 0.5284 - Recall: 0.2551 - accuracy: 0.4574 - loss: 1.0946
Epoch 4/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6442 - Precision: 0.5599 - Recall: 0.2498 - accuracy: 0.4548 - loss: 1.0909
Epoch 5/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6304 - Precision: 0.5429 - Recall: 0.2650 - accuracy: 0.4656 - loss: 1.0860
Epoch 6/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7133 - Precision: 0.6869 - Recall: 0.3296 - accuracy: 0.5408 - loss: 0.9811
Epoch 7/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7272 - Precision: 0.7034 - Recall: 0.3652 - accuracy: 0.5441 - loss: 0.9547
Epoch 8/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6952 - Precision: 0.6557 - Recall: 0.3156 - accuracy: 0.5208 - loss: 0.9719
Epoch 9/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7145 - Precision: 0.6644 - Recall: 0.2911 - accuracy: 0.5161 - loss: 0.9565
Epoch 10/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7487 - Precision: 0.7159 - Recall: 0.3336 - accuracy: 0.5729 - loss: 0.9171
Epoch 11/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.7371 - Precision: 0.7421 - Recall: 0.3393 - accuracy: 0.5180 - loss: 0.9363
Epoch 12/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7441 - Precision: 0.7172 - Recall: 0.3590 - accuracy: 0.5407 - loss: 0.9164
Epoch 13/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7931 - Precision: 0.7543 - Recall: 0.4173 - accuracy: 0.5988 - loss: 0.8358
Epoch 14/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7865 - Precision: 0.7505 - Recall: 0.3853 - accuracy: 0.5576 - loss: 0.8422
Epoch 15/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8034 - Precision: 0.8131 - Recall: 0.4314 - accuracy: 0.5954 - loss: 0.8124
Epoch 16/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8016 - Precision: 0.7389 - Recall: 0.3898 - accuracy: 0.5690 - loss: 0.7924
Epoch 17/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8334 - Precision: 0.8094 - Recall: 0.4273 - accuracy: 0.6102 - loss: 0.7351
Epoch 18/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8206 - Precision: 0.7773 - Recall: 0.4254 - accuracy: 0.5927 - loss: 0.7567
Epoch 19/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8455 - Precision: 0.7837 - Recall: 0.4609 - accuracy: 0.6183 - loss: 0.7075
Epoch 20/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8334 - Precision: 0.7973 - Recall: 0.4880 - accuracy: 0.6278 - loss: 0.7623
Epoch 21/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8380 - Precision: 0.7796 - Recall: 0.4526 - accuracy: 0.6115 - loss: 0.7400
Epoch 22/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8386 - Precision: 0.8089 - Recall: 0.4349 - accuracy: 0.6280 - loss: 0.7514
Epoch 23/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8553 - Precision: 0.7981 - Recall: 0.4663 - accuracy: 0.6370 - loss: 0.7137
Epoch 24/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8383 - Precision: 0.7808 - Recall: 0.4469 - accuracy: 0.6457 - loss: 0.7391
Epoch 25/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8527 - Precision: 0.8247 - Recall: 0.4834 - accuracy: 0.6265 - loss: 0.7044
Epoch 26/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8508 - Precision: 0.7940 - Recall: 0.4795 - accuracy: 0.6105 - loss: 0.7150
Epoch 27/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8570 - Precision: 0.8216 - Recall: 0.4939 - accuracy: 0.6437 - loss: 0.6963
Epoch 28/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8290 - Precision: 0.7362 - Recall: 0.4703 - accuracy: 0.6079 - loss: 0.7681
Epoch 29/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8747 - Precision: 0.8205 - Recall: 0.4895 - accuracy: 0.6362 - loss: 0.6566
Epoch 30/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8633 - Precision: 0.7968 - Recall: 0.4959 - accuracy: 0.6320 - loss: 0.6516
Epoch 31/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8605 - Precision: 0.7903 - Recall: 0.4867 - accuracy: 0.6498 - loss: 0.6918
Epoch 32/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8728 - Precision: 0.7984 - Recall: 0.5148 - accuracy: 0.6617 - loss: 0.6690
Epoch 33/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8768 - Precision: 0.8148 - Recall: 0.5183 - accuracy: 0.7112 - loss: 0.7215
Epoch 34/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8663 - Precision: 0.7680 - Recall: 0.4778 - accuracy: 0.6137 - loss: 0.6672
Epoch 35/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8617 - Precision: 0.7667 - Recall: 0.4904 - accuracy: 0.6491 - loss: 0.6844
Epoch 36/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8741 - Precision: 0.7693 - Recall: 0.5012 - accuracy: 0.6654 - loss: 0.6707
Epoch 37/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8738 - Precision: 0.7832 - Recall: 0.4999 - accuracy: 0.6645 - loss: 0.6619
Epoch 38/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.8649 - Precision: 0.7855 - Recall: 0.4662 - accuracy: 0.6439 - loss: 0.6695
Epoch 39/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8782 - Precision: 0.8116 - Recall: 0.4811 - accuracy: 0.6845 - loss: 0.6404
Epoch 40/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8919 - Precision: 0.7753 - Recall: 0.5141 - accuracy: 0.6813 - loss: 0.6029
Epoch 41/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8556 - Precision: 0.7501 - Recall: 0.4891 - accuracy: 0.6686 - loss: 0.7485
Epoch 42/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8824 - Precision: 0.8017 - Recall: 0.5215 - accuracy: 0.6691 - loss: 0.6264
Epoch 43/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8997 - Precision: 0.7869 - Recall: 0.5208 - accuracy: 0.6811 - loss: 0.5780
Epoch 44/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8843 - Precision: 0.8174 - Recall: 0.5372 - accuracy: 0.6569 - loss: 0.6136
Epoch 45/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8893 - Precision: 0.8009 - Recall: 0.5549 - accuracy: 0.7069 - loss: 0.6137
Epoch 46/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8901 - Precision: 0.7959 - Recall: 0.5572 - accuracy: 0.6744 - loss: 0.6103
Epoch 47/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8825 - Precision: 0.7971 - Recall: 0.5260 - accuracy: 0.6943 - loss: 0.6115
Epoch 48/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9056 - Precision: 0.8212 - Recall: 0.5726 - accuracy: 0.7022 - loss: 0.5757
Epoch 49/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8857 - Precision: 0.7777 - Recall: 0.5455 - accuracy: 0.6757 - loss: 0.6569
Epoch 50/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8857 - Precision: 0.8173 - Recall: 0.5209 - accuracy: 0.6976 - loss: 0.6217
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 27ms/step
Epoch 1/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 4s 4ms/step - AUC: 0.4788 - Precision: 0.3106 - Recall: 0.2588 - accuracy: 0.3344 - loss: 3.4376
Epoch 2/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5251 - Precision: 0.3672 - Recall: 0.2702 - accuracy: 0.3468 - loss: 2.0949
Epoch 3/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.5684 - Precision: 0.4074 - Recall: 0.2612 - accuracy: 0.4021 - loss: 1.5617
Epoch 4/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5633 - Precision: 0.4320 - Recall: 0.2744 - accuracy: 0.4130 - loss: 1.5164
Epoch 5/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5648 - Precision: 0.4359 - Recall: 0.2532 - accuracy: 0.4165 - loss: 1.5005
Epoch 6/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5692 - Precision: 0.4039 - Recall: 0.2227 - accuracy: 0.4140 - loss: 1.3130
Epoch 7/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5655 - Precision: 0.3732 - Recall: 0.1605 - accuracy: 0.4326 - loss: 1.3047
Epoch 8/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6134 - Precision: 0.4229 - Recall: 0.1935 - accuracy: 0.4773 - loss: 1.1404
Epoch 9/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6186 - Precision: 0.4355 - Recall: 0.1861 - accuracy: 0.4598 - loss: 1.1102
Epoch 10/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5547 - Precision: 0.3682 - Recall: 0.1262 - accuracy: 0.4264 - loss: 1.2085
Epoch 11/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6066 - Precision: 0.4633 - Recall: 0.1971 - accuracy: 0.4471 - loss: 1.1283
Epoch 12/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6126 - Precision: 0.4478 - Recall: 0.1929 - accuracy: 0.4826 - loss: 1.1202
Epoch 13/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6294 - Precision: 0.5069 - Recall: 0.1629 - accuracy: 0.4888 - loss: 1.1032
Epoch 14/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5538 - Precision: 0.3754 - Recall: 0.1215 - accuracy: 0.4066 - loss: 1.1684
Epoch 15/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.6388 - Precision: 0.5367 - Recall: 0.2047 - accuracy: 0.4992 - loss: 1.0604
Epoch 16/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6111 - Precision: 0.4824 - Recall: 0.1818 - accuracy: 0.4561 - loss: 1.0939
Epoch 17/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6137 - Precision: 0.4361 - Recall: 0.1248 - accuracy: 0.4790 - loss: 1.0943
Epoch 18/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6040 - Precision: 0.4929 - Recall: 0.1563 - accuracy: 0.5050 - loss: 1.0948
Epoch 19/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6194 - Precision: 0.4257 - Recall: 0.1177 - accuracy: 0.4749 - loss: 1.0810
Epoch 20/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6082 - Precision: 0.4785 - Recall: 0.1463 - accuracy: 0.4658 - loss: 1.0974
Epoch 21/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.5975 - Precision: 0.4915 - Recall: 0.1646 - accuracy: 0.4572 - loss: 1.1039
Epoch 22/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6301 - Precision: 0.5467 - Recall: 0.1576 - accuracy: 0.4934 - loss: 1.0579
Epoch 23/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5855 - Precision: 0.4138 - Recall: 0.1078 - accuracy: 0.4632 - loss: 1.1147
Epoch 24/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.6111 - Precision: 0.5036 - Recall: 0.1269 - accuracy: 0.4842 - loss: 1.0666
Epoch 25/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6223 - Precision: 0.4711 - Recall: 0.1458 - accuracy: 0.4727 - loss: 1.0767
Epoch 26/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6337 - Precision: 0.4913 - Recall: 0.1716 - accuracy: 0.5161 - loss: 1.0806
Epoch 27/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6625 - Precision: 0.5639 - Recall: 0.1814 - accuracy: 0.5276 - loss: 1.0262
Epoch 28/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6345 - Precision: 0.5261 - Recall: 0.1304 - accuracy: 0.4916 - loss: 1.0429
Epoch 29/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6080 - Precision: 0.5031 - Recall: 0.1366 - accuracy: 0.4740 - loss: 1.0747
Epoch 30/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6336 - Precision: 0.4762 - Recall: 0.1108 - accuracy: 0.5168 - loss: 1.0720
Epoch 31/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6235 - Precision: 0.4911 - Recall: 0.1329 - accuracy: 0.5020 - loss: 1.0566
Epoch 32/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6132 - Precision: 0.4356 - Recall: 0.1293 - accuracy: 0.4820 - loss: 1.0622
Epoch 33/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6239 - Precision: 0.5276 - Recall: 0.1837 - accuracy: 0.4723 - loss: 1.0707
Epoch 34/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6332 - Precision: 0.4980 - Recall: 0.1544 - accuracy: 0.5000 - loss: 1.0474
Epoch 35/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6560 - Precision: 0.6655 - Recall: 0.1632 - accuracy: 0.5129 - loss: 1.0170
Epoch 36/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6067 - Precision: 0.4787 - Recall: 0.1725 - accuracy: 0.4637 - loss: 1.0628
Epoch 37/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6105 - Precision: 0.5024 - Recall: 0.1551 - accuracy: 0.4884 - loss: 1.0558
Epoch 38/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6640 - Precision: 0.6219 - Recall: 0.2368 - accuracy: 0.4970 - loss: 1.0245
Epoch 39/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.6357 - Precision: 0.5517 - Recall: 0.1350 - accuracy: 0.5144 - loss: 1.0464
Epoch 40/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6675 - Precision: 0.6592 - Recall: 0.2166 - accuracy: 0.5155 - loss: 1.0248
Epoch 41/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6638 - Precision: 0.5889 - Recall: 0.1692 - accuracy: 0.5104 - loss: 1.0267
Epoch 42/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.6428 - Precision: 0.6511 - Recall: 0.1525 - accuracy: 0.4782 - loss: 1.0271
Epoch 43/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6381 - Precision: 0.5646 - Recall: 0.1546 - accuracy: 0.4955 - loss: 1.0589
Epoch 44/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.6584 - Precision: 0.6201 - Recall: 0.1714 - accuracy: 0.4905 - loss: 1.0159
Epoch 45/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.6427 - Precision: 0.5831 - Recall: 0.2118 - accuracy: 0.4789 - loss: 1.0424
Epoch 46/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6356 - Precision: 0.5890 - Recall: 0.1668 - accuracy: 0.4894 - loss: 1.0337
Epoch 47/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6708 - Precision: 0.6530 - Recall: 0.2212 - accuracy: 0.4940 - loss: 1.0014
Epoch 48/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.6777 - Precision: 0.6574 - Recall: 0.2400 - accuracy: 0.4897 - loss: 1.0030
Epoch 49/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6920 - Precision: 0.6666 - Recall: 0.2292 - accuracy: 0.5176 - loss: 0.9820
Epoch 50/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6992 - Precision: 0.7359 - Recall: 0.2762 - accuracy: 0.5005 - loss: 0.9544
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step
Epoch 1/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 4s 4ms/step - AUC: 0.5266 - Precision: 0.3601 - Recall: 0.3260 - accuracy: 0.3525 - loss: 4.1864
Epoch 2/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.4587 - Precision: 0.2910 - Recall: 0.2348 - accuracy: 0.2992 - loss: 2.9254
Epoch 3/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5052 - Precision: 0.3139 - Recall: 0.2177 - accuracy: 0.3226 - loss: 1.9989
Epoch 4/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5566 - Precision: 0.4041 - Recall: 0.2703 - accuracy: 0.3955 - loss: 1.7828
Epoch 5/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5676 - Precision: 0.4244 - Recall: 0.2701 - accuracy: 0.3955 - loss: 1.4747
Epoch 6/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5771 - Precision: 0.4581 - Recall: 0.2955 - accuracy: 0.3935 - loss: 1.3845
Epoch 7/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6285 - Precision: 0.4837 - Recall: 0.2573 - accuracy: 0.4875 - loss: 1.3114
Epoch 8/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6024 - Precision: 0.4700 - Recall: 0.2241 - accuracy: 0.4571 - loss: 1.2845
Epoch 9/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5711 - Precision: 0.4116 - Recall: 0.2173 - accuracy: 0.4146 - loss: 1.2662
Epoch 10/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6039 - Precision: 0.4693 - Recall: 0.2435 - accuracy: 0.4573 - loss: 1.2054
Epoch 11/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6185 - Precision: 0.5255 - Recall: 0.2453 - accuracy: 0.4615 - loss: 1.1356
Epoch 12/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5530 - Precision: 0.3851 - Recall: 0.1686 - accuracy: 0.4190 - loss: 1.2441
Epoch 13/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5950 - Precision: 0.4399 - Recall: 0.1856 - accuracy: 0.4736 - loss: 1.1558
Epoch 14/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5842 - Precision: 0.4437 - Recall: 0.1810 - accuracy: 0.4417 - loss: 1.1654
Epoch 15/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6054 - Precision: 0.4712 - Recall: 0.1933 - accuracy: 0.4552 - loss: 1.1208
Epoch 16/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5977 - Precision: 0.4184 - Recall: 0.1583 - accuracy: 0.4668 - loss: 1.1354
Epoch 17/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6285 - Precision: 0.5404 - Recall: 0.1881 - accuracy: 0.5021 - loss: 1.0874
Epoch 18/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6665 - Precision: 0.5572 - Recall: 0.2233 - accuracy: 0.5216 - loss: 1.0252
Epoch 19/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5930 - Precision: 0.4251 - Recall: 0.1602 - accuracy: 0.4634 - loss: 1.1322
Epoch 20/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6037 - Precision: 0.4656 - Recall: 0.1893 - accuracy: 0.4764 - loss: 1.1020
Epoch 21/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6080 - Precision: 0.4962 - Recall: 0.1555 - accuracy: 0.4687 - loss: 1.0789
Epoch 22/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6021 - Precision: 0.4944 - Recall: 0.1910 - accuracy: 0.4688 - loss: 1.0779
Epoch 23/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6318 - Precision: 0.5336 - Recall: 0.1853 - accuracy: 0.4832 - loss: 1.0655
Epoch 24/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6257 - Precision: 0.5037 - Recall: 0.1791 - accuracy: 0.4654 - loss: 1.0653
Epoch 25/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5880 - Precision: 0.4398 - Recall: 0.1397 - accuracy: 0.4318 - loss: 1.1067
Epoch 26/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6438 - Precision: 0.5670 - Recall: 0.2235 - accuracy: 0.4798 - loss: 1.0420
Epoch 27/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6330 - Precision: 0.5518 - Recall: 0.2064 - accuracy: 0.4955 - loss: 1.0582
Epoch 28/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6013 - Precision: 0.4783 - Recall: 0.1375 - accuracy: 0.4810 - loss: 1.0718
Epoch 29/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6252 - Precision: 0.5778 - Recall: 0.1808 - accuracy: 0.4615 - loss: 1.0630
Epoch 30/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6222 - Precision: 0.5040 - Recall: 0.1975 - accuracy: 0.4591 - loss: 1.0633
Epoch 31/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6241 - Precision: 0.5470 - Recall: 0.1667 - accuracy: 0.4939 - loss: 1.0524
Epoch 32/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5817 - Precision: 0.3981 - Recall: 0.1114 - accuracy: 0.4619 - loss: 1.0900
Epoch 33/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6403 - Precision: 0.5573 - Recall: 0.1373 - accuracy: 0.5007 - loss: 1.0467
Epoch 34/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6229 - Precision: 0.5180 - Recall: 0.1618 - accuracy: 0.4677 - loss: 1.0488
Epoch 35/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6147 - Precision: 0.5210 - Recall: 0.1331 - accuracy: 0.4784 - loss: 1.0646
Epoch 36/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6295 - Precision: 0.5758 - Recall: 0.1526 - accuracy: 0.4790 - loss: 1.0588
Epoch 37/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6294 - Precision: 0.4964 - Recall: 0.1865 - accuracy: 0.4903 - loss: 1.0605
Epoch 38/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6000 - Precision: 0.5375 - Recall: 0.1561 - accuracy: 0.4796 - loss: 1.0715
Epoch 39/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6604 - Precision: 0.5828 - Recall: 0.2018 - accuracy: 0.5154 - loss: 1.0249
Epoch 40/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6045 - Precision: 0.4729 - Recall: 0.1347 - accuracy: 0.4997 - loss: 1.0636
Epoch 41/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6128 - Precision: 0.5012 - Recall: 0.1104 - accuracy: 0.4660 - loss: 1.0695
Epoch 42/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6259 - Precision: 0.5150 - Recall: 0.1894 - accuracy: 0.4993 - loss: 1.0567
Epoch 43/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6419 - Precision: 0.5451 - Recall: 0.2032 - accuracy: 0.4866 - loss: 1.0365
Epoch 44/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6475 - Precision: 0.5669 - Recall: 0.2133 - accuracy: 0.5147 - loss: 1.0312
Epoch 45/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6175 - Precision: 0.5442 - Recall: 0.1839 - accuracy: 0.4652 - loss: 1.0570
Epoch 46/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6059 - Precision: 0.4787 - Recall: 0.1703 - accuracy: 0.4754 - loss: 1.0625
Epoch 47/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6573 - Precision: 0.5945 - Recall: 0.2144 - accuracy: 0.5285 - loss: 1.0237
Epoch 48/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6431 - Precision: 0.5504 - Recall: 0.1796 - accuracy: 0.5150 - loss: 1.0266
Epoch 49/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6577 - Precision: 0.5793 - Recall: 0.2104 - accuracy: 0.5255 - loss: 1.0207
Epoch 50/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6270 - Precision: 0.5357 - Recall: 0.1430 - accuracy: 0.4812 - loss: 1.0438
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 43ms/step
Epoch 1/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 6s 5ms/step - AUC: 0.4536 - Precision: 0.2584 - Recall: 0.2272 - accuracy: 0.2788 - loss: 4.9837
Epoch 2/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5171 - Precision: 0.3257 - Recall: 0.2724 - accuracy: 0.3236 - loss: 3.0947
Epoch 3/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5076 - Precision: 0.3473 - Recall: 0.2911 - accuracy: 0.3522 - loss: 2.7684
Epoch 4/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5767 - Precision: 0.3967 - Recall: 0.3305 - accuracy: 0.3927 - loss: 2.1010
Epoch 5/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.5320 - Precision: 0.3778 - Recall: 0.2759 - accuracy: 0.3751 - loss: 1.9529
Epoch 6/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5503 - Precision: 0.4021 - Recall: 0.3051 - accuracy: 0.3838 - loss: 2.0298
Epoch 7/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.5551 - Precision: 0.3913 - Recall: 0.2862 - accuracy: 0.3762 - loss: 1.8280
Epoch 8/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5753 - Precision: 0.4273 - Recall: 0.2909 - accuracy: 0.4221 - loss: 1.4770
Epoch 9/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5573 - Precision: 0.3655 - Recall: 0.2247 - accuracy: 0.3789 - loss: 1.5277
Epoch 10/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5667 - Precision: 0.3962 - Recall: 0.2301 - accuracy: 0.4055 - loss: 1.4553
Epoch 11/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5339 - Precision: 0.3695 - Recall: 0.2250 - accuracy: 0.3709 - loss: 1.4424
Epoch 12/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5853 - Precision: 0.4486 - Recall: 0.2243 - accuracy: 0.4294 - loss: 1.2468
Epoch 13/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6130 - Precision: 0.4523 - Recall: 0.2282 - accuracy: 0.4373 - loss: 1.1891
Epoch 14/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6040 - Precision: 0.4501 - Recall: 0.2174 - accuracy: 0.4345 - loss: 1.1953
Epoch 15/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5445 - Precision: 0.3814 - Recall: 0.1572 - accuracy: 0.3794 - loss: 1.2868
Epoch 16/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6056 - Precision: 0.5187 - Recall: 0.2236 - accuracy: 0.4652 - loss: 1.1604
Epoch 17/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5810 - Precision: 0.5169 - Recall: 0.2252 - accuracy: 0.4465 - loss: 1.1878
Epoch 18/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6078 - Precision: 0.4603 - Recall: 0.1901 - accuracy: 0.4500 - loss: 1.1453
Epoch 19/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5870 - Precision: 0.4597 - Recall: 0.1857 - accuracy: 0.4597 - loss: 1.2161
Epoch 20/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5944 - Precision: 0.4647 - Recall: 0.2003 - accuracy: 0.4588 - loss: 1.1683
Epoch 21/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6151 - Precision: 0.5267 - Recall: 0.2009 - accuracy: 0.4535 - loss: 1.1430
Epoch 22/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6427 - Precision: 0.5210 - Recall: 0.2097 - accuracy: 0.4878 - loss: 1.0916
Epoch 23/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6289 - Precision: 0.5239 - Recall: 0.2369 - accuracy: 0.4733 - loss: 1.1022
Epoch 24/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6050 - Precision: 0.4489 - Recall: 0.1839 - accuracy: 0.4155 - loss: 1.1121
Epoch 25/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6171 - Precision: 0.4915 - Recall: 0.2215 - accuracy: 0.4422 - loss: 1.0979
Epoch 26/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6069 - Precision: 0.4804 - Recall: 0.1756 - accuracy: 0.4663 - loss: 1.1169
Epoch 27/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6132 - Precision: 0.5338 - Recall: 0.1997 - accuracy: 0.4377 - loss: 1.1161
Epoch 28/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6030 - Precision: 0.5368 - Recall: 0.2394 - accuracy: 0.4396 - loss: 1.1474
Epoch 29/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5895 - Precision: 0.3978 - Recall: 0.1549 - accuracy: 0.4314 - loss: 1.1233
Epoch 30/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5996 - Precision: 0.4723 - Recall: 0.1649 - accuracy: 0.4328 - loss: 1.1176
Epoch 31/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6296 - Precision: 0.5477 - Recall: 0.1737 - accuracy: 0.4951 - loss: 1.0709
Epoch 32/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6179 - Precision: 0.5609 - Recall: 0.1958 - accuracy: 0.4623 - loss: 1.0940
Epoch 33/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6105 - Precision: 0.5092 - Recall: 0.1932 - accuracy: 0.4445 - loss: 1.1028
Epoch 34/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6112 - Precision: 0.5486 - Recall: 0.1943 - accuracy: 0.4429 - loss: 1.0868
Epoch 35/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6211 - Precision: 0.4652 - Recall: 0.1787 - accuracy: 0.4896 - loss: 1.1147
Epoch 36/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6161 - Precision: 0.5055 - Recall: 0.1836 - accuracy: 0.4793 - loss: 1.0821
Epoch 37/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6589 - Precision: 0.5854 - Recall: 0.2231 - accuracy: 0.4855 - loss: 1.0343
Epoch 38/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6004 - Precision: 0.5353 - Recall: 0.1827 - accuracy: 0.4107 - loss: 1.0990
Epoch 39/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6325 - Precision: 0.4721 - Recall: 0.1715 - accuracy: 0.4996 - loss: 1.0697
Epoch 40/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6705 - Precision: 0.6280 - Recall: 0.1999 - accuracy: 0.5196 - loss: 1.0187
Epoch 41/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6410 - Precision: 0.5111 - Recall: 0.1326 - accuracy: 0.4704 - loss: 1.0643
Epoch 42/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6166 - Precision: 0.4720 - Recall: 0.1725 - accuracy: 0.4640 - loss: 1.0795
Epoch 43/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6514 - Precision: 0.5813 - Recall: 0.2199 - accuracy: 0.4962 - loss: 1.0363
Epoch 44/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6292 - Precision: 0.5844 - Recall: 0.2093 - accuracy: 0.4962 - loss: 1.0529
Epoch 45/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6189 - Precision: 0.5687 - Recall: 0.1589 - accuracy: 0.4638 - loss: 1.0698
Epoch 46/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6420 - Precision: 0.5787 - Recall: 0.1828 - accuracy: 0.5106 - loss: 1.0599
Epoch 47/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6260 - Precision: 0.5371 - Recall: 0.1700 - accuracy: 0.5210 - loss: 1.0574
Epoch 48/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6846 - Precision: 0.6497 - Recall: 0.2557 - accuracy: 0.5065 - loss: 1.0111
Epoch 49/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6628 - Precision: 0.5825 - Recall: 0.2338 - accuracy: 0.5086 - loss: 1.0247
Epoch 50/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6393 - Precision: 0.5805 - Recall: 0.2243 - accuracy: 0.4822 - loss: 1.0493
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 32ms/step
Epoch 1/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 4s 4ms/step - AUC: 0.6710 - Precision: 0.5363 - Recall: 0.2895 - accuracy: 0.4543 - loss: 1.1222
Epoch 2/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7924 - Precision: 0.7329 - Recall: 0.3794 - accuracy: 0.5931 - loss: 0.8486
Epoch 3/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7678 - Precision: 0.6904 - Recall: 0.3587 - accuracy: 0.5607 - loss: 0.9036
Epoch 4/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7886 - Precision: 0.7464 - Recall: 0.3772 - accuracy: 0.5941 - loss: 0.8546
Epoch 5/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7783 - Precision: 0.7788 - Recall: 0.3776 - accuracy: 0.5481 - loss: 0.8468
Epoch 6/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7755 - Precision: 0.8398 - Recall: 0.3354 - accuracy: 0.5659 - loss: 0.9422
Epoch 7/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7815 - Precision: 0.7624 - Recall: 0.3415 - accuracy: 0.5584 - loss: 0.8531
Epoch 8/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8177 - Precision: 0.7940 - Recall: 0.3821 - accuracy: 0.6192 - loss: 0.9072
Epoch 9/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8063 - Precision: 0.8467 - Recall: 0.3390 - accuracy: 0.5922 - loss: 0.8252
Epoch 10/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7859 - Precision: 0.7397 - Recall: 0.3883 - accuracy: 0.5716 - loss: 0.9559
Epoch 11/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.8385 - Precision: 0.8391 - Recall: 0.4402 - accuracy: 0.6610 - loss: 0.7775
Epoch 12/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.8197 - Precision: 0.7846 - Recall: 0.4078 - accuracy: 0.6241 - loss: 0.8529
Epoch 13/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7754 - Precision: 0.7672 - Recall: 0.2615 - accuracy: 0.5832 - loss: 0.9623
Epoch 14/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.7896 - Precision: 0.7744 - Recall: 0.3659 - accuracy: 0.5626 - loss: 0.8401
Epoch 15/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.8361 - Precision: 0.7903 - Recall: 0.4179 - accuracy: 0.6409 - loss: 0.7698
Epoch 16/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.8150 - Precision: 0.8314 - Recall: 0.4033 - accuracy: 0.5966 - loss: 0.7980
Epoch 17/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.8203 - Precision: 0.8129 - Recall: 0.4109 - accuracy: 0.5856 - loss: 0.8142
Epoch 18/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.7996 - Precision: 0.7852 - Recall: 0.3690 - accuracy: 0.5740 - loss: 0.8503
Epoch 19/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7928 - Precision: 0.7900 - Recall: 0.3304 - accuracy: 0.5704 - loss: 0.8519
Epoch 20/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.8322 - Precision: 0.8252 - Recall: 0.4465 - accuracy: 0.6370 - loss: 0.7646
Epoch 21/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8123 - Precision: 0.8123 - Recall: 0.3732 - accuracy: 0.6175 - loss: 0.8204
Epoch 22/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.8299 - Precision: 0.7884 - Recall: 0.3958 - accuracy: 0.6270 - loss: 0.7845
Epoch 23/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8147 - Precision: 0.7437 - Recall: 0.3957 - accuracy: 0.5806 - loss: 0.8160
Epoch 24/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7805 - Precision: 0.8077 - Recall: 0.3227 - accuracy: 0.5417 - loss: 0.8339
Epoch 25/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7965 - Precision: 0.7533 - Recall: 0.3840 - accuracy: 0.5654 - loss: 0.8254
Epoch 26/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8278 - Precision: 0.7729 - Recall: 0.4305 - accuracy: 0.6208 - loss: 0.7839
Epoch 27/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.7916 - Precision: 0.7163 - Recall: 0.3533 - accuracy: 0.5704 - loss: 0.9116
Epoch 28/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.8216 - Precision: 0.7889 - Recall: 0.4169 - accuracy: 0.5981 - loss: 0.7863
Epoch 29/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8039 - Precision: 0.7262 - Recall: 0.4204 - accuracy: 0.5730 - loss: 0.8324
Epoch 30/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7879 - Precision: 0.7902 - Recall: 0.3389 - accuracy: 0.5906 - loss: 0.9412
Epoch 31/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.8143 - Precision: 0.8097 - Recall: 0.3937 - accuracy: 0.6060 - loss: 0.7951
Epoch 32/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8079 - Precision: 0.7256 - Recall: 0.3942 - accuracy: 0.5928 - loss: 0.8825
Epoch 33/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8188 - Precision: 0.7680 - Recall: 0.4077 - accuracy: 0.5920 - loss: 0.8285
Epoch 34/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.8217 - Precision: 0.7975 - Recall: 0.3931 - accuracy: 0.5783 - loss: 0.8115
Epoch 35/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8012 - Precision: 0.7769 - Recall: 0.4433 - accuracy: 0.6025 - loss: 0.8367
Epoch 36/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8159 - Precision: 0.7260 - Recall: 0.4244 - accuracy: 0.6245 - loss: 0.9376
Epoch 37/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7896 - Precision: 0.7438 - Recall: 0.3485 - accuracy: 0.6173 - loss: 0.9829
Epoch 38/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7676 - Precision: 0.7082 - Recall: 0.3774 - accuracy: 0.5877 - loss: 0.9076
Epoch 39/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7474 - Precision: 0.7270 - Recall: 0.4120 - accuracy: 0.5567 - loss: 0.9420
Epoch 40/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7733 - Precision: 0.7286 - Recall: 0.4341 - accuracy: 0.5846 - loss: 0.8917
Epoch 41/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7767 - Precision: 0.7867 - Recall: 0.4049 - accuracy: 0.5782 - loss: 0.8606
Epoch 42/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7210 - Precision: 0.7715 - Recall: 0.3422 - accuracy: 0.5224 - loss: 0.9339
Epoch 43/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.8248 - Precision: 0.8134 - Recall: 0.4608 - accuracy: 0.6238 - loss: 0.8029
Epoch 44/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7386 - Precision: 0.6928 - Recall: 0.3848 - accuracy: 0.5430 - loss: 0.9649
Epoch 45/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7964 - Precision: 0.7354 - Recall: 0.4606 - accuracy: 0.6375 - loss: 0.9191
Epoch 46/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7280 - Precision: 0.6100 - Recall: 0.3959 - accuracy: 0.5532 - loss: 0.9612
Epoch 47/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6970 - Precision: 0.5769 - Recall: 0.4284 - accuracy: 0.5389 - loss: 1.0102
Epoch 48/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7075 - Precision: 0.6350 - Recall: 0.4362 - accuracy: 0.5187 - loss: 0.9996
Epoch 49/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7345 - Precision: 0.7030 - Recall: 0.4512 - accuracy: 0.5726 - loss: 0.9138
Epoch 50/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7427 - Precision: 0.7587 - Recall: 0.3440 - accuracy: 0.5199 - loss: 0.9196
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 28ms/step
Epoch 1/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 4s 4ms/step - AUC: 0.7183 - Precision: 0.5622 - Recall: 0.3940 - accuracy: 0.5211 - loss: 1.1014
Epoch 2/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7608 - Precision: 0.7914 - Recall: 0.3119 - accuracy: 0.5368 - loss: 0.8775
Epoch 3/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8216 - Precision: 0.7385 - Recall: 0.4388 - accuracy: 0.6160 - loss: 0.8016
Epoch 4/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8553 - Precision: 0.7800 - Recall: 0.4725 - accuracy: 0.6450 - loss: 0.7310
Epoch 5/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8572 - Precision: 0.7318 - Recall: 0.4864 - accuracy: 0.6462 - loss: 0.6976
Epoch 6/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8337 - Precision: 0.7983 - Recall: 0.4396 - accuracy: 0.6180 - loss: 0.7753
Epoch 7/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8386 - Precision: 0.7491 - Recall: 0.4253 - accuracy: 0.6451 - loss: 0.7789
Epoch 8/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8824 - Precision: 0.7882 - Recall: 0.5398 - accuracy: 0.6802 - loss: 0.6582
Epoch 9/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.8617 - Precision: 0.7843 - Recall: 0.4882 - accuracy: 0.6380 - loss: 0.6849
Epoch 10/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8819 - Precision: 0.7817 - Recall: 0.5682 - accuracy: 0.7122 - loss: 0.6786
Epoch 11/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.8830 - Precision: 0.7788 - Recall: 0.5579 - accuracy: 0.7022 - loss: 0.6651
Epoch 12/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.8556 - Precision: 0.8025 - Recall: 0.5301 - accuracy: 0.6912 - loss: 0.7784
Epoch 13/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8966 - Precision: 0.8084 - Recall: 0.5866 - accuracy: 0.7181 - loss: 0.6317
Epoch 14/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8882 - Precision: 0.8215 - Recall: 0.5693 - accuracy: 0.7022 - loss: 0.6331
Epoch 15/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8681 - Precision: 0.7959 - Recall: 0.4623 - accuracy: 0.6756 - loss: 0.6956
Epoch 16/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8566 - Precision: 0.7869 - Recall: 0.5014 - accuracy: 0.6580 - loss: 0.7506
Epoch 17/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8597 - Precision: 0.7821 - Recall: 0.4670 - accuracy: 0.6722 - loss: 0.7392
Epoch 18/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8009 - Precision: 0.7052 - Recall: 0.3687 - accuracy: 0.6217 - loss: 0.9317
Epoch 19/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8740 - Precision: 0.8249 - Recall: 0.5162 - accuracy: 0.6884 - loss: 0.7054
Epoch 20/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8527 - Precision: 0.7590 - Recall: 0.5121 - accuracy: 0.6528 - loss: 0.7077
Epoch 21/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8849 - Precision: 0.7602 - Recall: 0.5773 - accuracy: 0.6866 - loss: 0.6438
Epoch 22/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8541 - Precision: 0.7266 - Recall: 0.4842 - accuracy: 0.6456 - loss: 0.7019
Epoch 23/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8584 - Precision: 0.7577 - Recall: 0.4771 - accuracy: 0.6394 - loss: 0.7282
Epoch 24/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8904 - Precision: 0.7969 - Recall: 0.5787 - accuracy: 0.7021 - loss: 0.6186
Epoch 25/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8776 - Precision: 0.7657 - Recall: 0.5105 - accuracy: 0.6630 - loss: 0.6628
Epoch 26/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.8781 - Precision: 0.7904 - Recall: 0.5191 - accuracy: 0.6769 - loss: 0.6430
Epoch 27/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8792 - Precision: 0.8284 - Recall: 0.5241 - accuracy: 0.6637 - loss: 0.6369
Epoch 28/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8893 - Precision: 0.7720 - Recall: 0.6044 - accuracy: 0.7056 - loss: 0.6355
Epoch 29/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8596 - Precision: 0.7731 - Recall: 0.4467 - accuracy: 0.6593 - loss: 0.7367
Epoch 30/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8772 - Precision: 0.8051 - Recall: 0.4784 - accuracy: 0.6992 - loss: 0.6575
Epoch 31/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8827 - Precision: 0.7692 - Recall: 0.5179 - accuracy: 0.6647 - loss: 0.6603
Epoch 32/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8536 - Precision: 0.7760 - Recall: 0.5140 - accuracy: 0.6247 - loss: 0.6807
Epoch 33/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8617 - Precision: 0.8130 - Recall: 0.4715 - accuracy: 0.6494 - loss: 0.6806
Epoch 34/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8763 - Precision: 0.8483 - Recall: 0.4904 - accuracy: 0.6651 - loss: 0.6730
Epoch 35/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.8703 - Precision: 0.8173 - Recall: 0.4916 - accuracy: 0.6615 - loss: 0.6836
Epoch 36/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.8847 - Precision: 0.8049 - Recall: 0.5411 - accuracy: 0.6975 - loss: 0.6716
Epoch 37/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8546 - Precision: 0.8072 - Recall: 0.4194 - accuracy: 0.6653 - loss: 0.7187
Epoch 38/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8613 - Precision: 0.7844 - Recall: 0.4929 - accuracy: 0.6413 - loss: 0.6773
Epoch 39/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8583 - Precision: 0.8058 - Recall: 0.4772 - accuracy: 0.6440 - loss: 0.7259
Epoch 40/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8760 - Precision: 0.7904 - Recall: 0.5290 - accuracy: 0.6819 - loss: 0.6803
Epoch 41/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8665 - Precision: 0.7932 - Recall: 0.5133 - accuracy: 0.6619 - loss: 0.6688
Epoch 42/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8580 - Precision: 0.7360 - Recall: 0.4930 - accuracy: 0.6178 - loss: 0.6786
Epoch 43/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8831 - Precision: 0.8103 - Recall: 0.5138 - accuracy: 0.6636 - loss: 0.6439
Epoch 44/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8890 - Precision: 0.7835 - Recall: 0.5880 - accuracy: 0.6944 - loss: 0.6540
Epoch 45/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8727 - Precision: 0.8424 - Recall: 0.5000 - accuracy: 0.6627 - loss: 0.6661
Epoch 46/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8551 - Precision: 0.7892 - Recall: 0.4964 - accuracy: 0.6519 - loss: 0.7452
Epoch 47/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8601 - Precision: 0.8029 - Recall: 0.5195 - accuracy: 0.6521 - loss: 0.7035
Epoch 48/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8693 - Precision: 0.7636 - Recall: 0.5103 - accuracy: 0.6580 - loss: 0.6757
Epoch 49/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8900 - Precision: 0.7905 - Recall: 0.5467 - accuracy: 0.6878 - loss: 0.6023
Epoch 50/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8405 - Precision: 0.7851 - Recall: 0.3999 - accuracy: 0.6274 - loss: 0.7284
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 28ms/step
Epoch 1/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 4s 4ms/step - AUC: 0.6145 - Precision: 0.5017 - Recall: 0.2747 - accuracy: 0.4302 - loss: 1.1356
Epoch 2/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8271 - Precision: 0.7650 - Recall: 0.4831 - accuracy: 0.6342 - loss: 0.8030
Epoch 3/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8189 - Precision: 0.7072 - Recall: 0.4821 - accuracy: 0.6221 - loss: 0.8247
Epoch 4/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8470 - Precision: 0.7796 - Recall: 0.4443 - accuracy: 0.6470 - loss: 0.7259
Epoch 5/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8453 - Precision: 0.7536 - Recall: 0.4875 - accuracy: 0.6282 - loss: 0.7098
Epoch 6/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8731 - Precision: 0.7486 - Recall: 0.5321 - accuracy: 0.6646 - loss: 0.6696
Epoch 7/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8748 - Precision: 0.8215 - Recall: 0.4685 - accuracy: 0.6618 - loss: 0.6639
Epoch 8/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8765 - Precision: 0.7674 - Recall: 0.4973 - accuracy: 0.6759 - loss: 0.6487
Epoch 9/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8773 - Precision: 0.7936 - Recall: 0.5148 - accuracy: 0.6571 - loss: 0.6332
Epoch 10/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8842 - Precision: 0.7902 - Recall: 0.5563 - accuracy: 0.6923 - loss: 0.6368
Epoch 11/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8849 - Precision: 0.8002 - Recall: 0.5435 - accuracy: 0.6897 - loss: 0.6280
Epoch 12/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8849 - Precision: 0.7759 - Recall: 0.5003 - accuracy: 0.7027 - loss: 0.6406
Epoch 13/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8722 - Precision: 0.7413 - Recall: 0.4959 - accuracy: 0.6323 - loss: 0.6353
Epoch 14/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8563 - Precision: 0.7618 - Recall: 0.4557 - accuracy: 0.6173 - loss: 0.6836
Epoch 15/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8828 - Precision: 0.7501 - Recall: 0.5383 - accuracy: 0.6769 - loss: 0.6197
Epoch 16/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8826 - Precision: 0.7630 - Recall: 0.5416 - accuracy: 0.6632 - loss: 0.6128
Epoch 17/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.8975 - Precision: 0.8175 - Recall: 0.5369 - accuracy: 0.6714 - loss: 0.5799
Epoch 18/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8750 - Precision: 0.7309 - Recall: 0.4909 - accuracy: 0.6492 - loss: 0.6143
Epoch 19/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9140 - Precision: 0.8131 - Recall: 0.6243 - accuracy: 0.7287 - loss: 0.5298
Epoch 20/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.8946 - Precision: 0.7568 - Recall: 0.6032 - accuracy: 0.6995 - loss: 0.5868
Epoch 21/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.8927 - Precision: 0.8353 - Recall: 0.5275 - accuracy: 0.6924 - loss: 0.6043
Epoch 22/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8922 - Precision: 0.7543 - Recall: 0.5992 - accuracy: 0.6874 - loss: 0.5925
Epoch 23/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9040 - Precision: 0.8146 - Recall: 0.5952 - accuracy: 0.7437 - loss: 0.5837
Epoch 24/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.8852 - Precision: 0.7150 - Recall: 0.5774 - accuracy: 0.6636 - loss: 0.6157
Epoch 25/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8909 - Precision: 0.7509 - Recall: 0.5385 - accuracy: 0.6602 - loss: 0.5918
Epoch 26/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8850 - Precision: 0.7738 - Recall: 0.5275 - accuracy: 0.6789 - loss: 0.6319
Epoch 27/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8910 - Precision: 0.8304 - Recall: 0.4950 - accuracy: 0.6662 - loss: 0.5859
Epoch 28/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9058 - Precision: 0.7599 - Recall: 0.6391 - accuracy: 0.7080 - loss: 0.5543
Epoch 29/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9106 - Precision: 0.8081 - Recall: 0.5788 - accuracy: 0.7403 - loss: 0.5490
Epoch 30/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8916 - Precision: 0.7714 - Recall: 0.5296 - accuracy: 0.6916 - loss: 0.5825
Epoch 31/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9088 - Precision: 0.7664 - Recall: 0.5802 - accuracy: 0.6812 - loss: 0.5068
Epoch 32/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9078 - Precision: 0.7708 - Recall: 0.6387 - accuracy: 0.7185 - loss: 0.5336
Epoch 33/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8851 - Precision: 0.7964 - Recall: 0.4753 - accuracy: 0.6821 - loss: 0.6078
Epoch 34/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9058 - Precision: 0.8233 - Recall: 0.5720 - accuracy: 0.7236 - loss: 0.5610
Epoch 35/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9132 - Precision: 0.7833 - Recall: 0.6478 - accuracy: 0.7339 - loss: 0.5403
Epoch 36/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8996 - Precision: 0.7728 - Recall: 0.5695 - accuracy: 0.7066 - loss: 0.5625
Epoch 37/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8830 - Precision: 0.7730 - Recall: 0.5142 - accuracy: 0.6471 - loss: 0.5960
Epoch 38/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.8712 - Precision: 0.7588 - Recall: 0.5024 - accuracy: 0.6468 - loss: 0.6988
Epoch 39/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9042 - Precision: 0.7681 - Recall: 0.6159 - accuracy: 0.7108 - loss: 0.5487
Epoch 40/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8912 - Precision: 0.8328 - Recall: 0.4874 - accuracy: 0.6579 - loss: 0.5943
Epoch 41/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8803 - Precision: 0.7326 - Recall: 0.5245 - accuracy: 0.6753 - loss: 0.6219
Epoch 42/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9018 - Precision: 0.7895 - Recall: 0.5862 - accuracy: 0.7133 - loss: 0.5753
Epoch 43/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8904 - Precision: 0.7167 - Recall: 0.5695 - accuracy: 0.6712 - loss: 0.5745
Epoch 44/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9025 - Precision: 0.7869 - Recall: 0.5772 - accuracy: 0.6995 - loss: 0.5425
Epoch 45/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9030 - Precision: 0.7597 - Recall: 0.6005 - accuracy: 0.7019 - loss: 0.5535
Epoch 46/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9024 - Precision: 0.7931 - Recall: 0.5897 - accuracy: 0.7047 - loss: 0.5713
Epoch 47/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8922 - Precision: 0.7569 - Recall: 0.5881 - accuracy: 0.6822 - loss: 0.5754
Epoch 48/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9049 - Precision: 0.8341 - Recall: 0.5015 - accuracy: 0.6981 - loss: 0.5389
Epoch 49/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8946 - Precision: 0.7490 - Recall: 0.5998 - accuracy: 0.6800 - loss: 0.5674
Epoch 50/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.9115 - Precision: 0.7869 - Recall: 0.5863 - accuracy: 0.7212 - loss: 0.5495
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 27ms/step
Epoch 1/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 5s 5ms/step - AUC: 0.6209 - Precision: 0.4823 - Recall: 0.3220 - accuracy: 0.4820 - loss: 1.3226
Epoch 2/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6900 - Precision: 0.6368 - Recall: 0.2966 - accuracy: 0.4955 - loss: 1.0366
Epoch 3/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6488 - Precision: 0.7328 - Recall: 0.2271 - accuracy: 0.4624 - loss: 1.0013
Epoch 4/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6805 - Precision: 0.7109 - Recall: 0.1997 - accuracy: 0.4873 - loss: 1.0544
Epoch 5/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7043 - Precision: 0.7989 - Recall: 0.2783 - accuracy: 0.4956 - loss: 0.9640
Epoch 6/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7462 - Precision: 0.7591 - Recall: 0.3076 - accuracy: 0.5442 - loss: 0.9284
Epoch 7/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7064 - Precision: 0.7219 - Recall: 0.2629 - accuracy: 0.5014 - loss: 1.0529
Epoch 8/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7315 - Precision: 0.8192 - Recall: 0.2936 - accuracy: 0.5628 - loss: 0.9448
Epoch 9/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7383 - Precision: 0.8322 - Recall: 0.2743 - accuracy: 0.5598 - loss: 0.9084
Epoch 10/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6690 - Precision: 0.7527 - Recall: 0.1780 - accuracy: 0.4702 - loss: 1.0044
Epoch 11/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6863 - Precision: 0.7274 - Recall: 0.2379 - accuracy: 0.4926 - loss: 0.9867
Epoch 12/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7387 - Precision: 0.8367 - Recall: 0.2854 - accuracy: 0.5361 - loss: 0.9004
Epoch 13/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7239 - Precision: 0.8443 - Recall: 0.2689 - accuracy: 0.5087 - loss: 1.0119
Epoch 14/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7272 - Precision: 0.8353 - Recall: 0.2583 - accuracy: 0.5434 - loss: 1.0155
Epoch 15/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6834 - Precision: 0.7992 - Recall: 0.2453 - accuracy: 0.4608 - loss: 0.9974
Epoch 16/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6849 - Precision: 0.8383 - Recall: 0.2096 - accuracy: 0.4682 - loss: 0.9755
Epoch 17/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.7329 - Precision: 0.8243 - Recall: 0.2777 - accuracy: 0.5303 - loss: 0.9114
Epoch 18/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6219 - Precision: 0.7362 - Recall: 0.1770 - accuracy: 0.4168 - loss: 1.0862
Epoch 19/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6514 - Precision: 0.7094 - Recall: 0.1921 - accuracy: 0.4348 - loss: 1.0854
Epoch 20/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6803 - Precision: 0.7788 - Recall: 0.1962 - accuracy: 0.4857 - loss: 1.1309
Epoch 21/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6946 - Precision: 0.8568 - Recall: 0.2332 - accuracy: 0.4823 - loss: 0.9442
Epoch 22/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7057 - Precision: 0.8625 - Recall: 0.2105 - accuracy: 0.5020 - loss: 0.9630
Epoch 23/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6919 - Precision: 0.8654 - Recall: 0.2284 - accuracy: 0.4572 - loss: 0.9404
Epoch 24/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6897 - Precision: 0.8304 - Recall: 0.2437 - accuracy: 0.4700 - loss: 0.9838
Epoch 25/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6709 - Precision: 0.8097 - Recall: 0.1810 - accuracy: 0.4821 - loss: 1.1119
Epoch 26/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7183 - Precision: 0.8288 - Recall: 0.2687 - accuracy: 0.5151 - loss: 0.9975
Epoch 27/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7017 - Precision: 0.7920 - Recall: 0.2362 - accuracy: 0.4989 - loss: 0.9550
Epoch 28/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7152 - Precision: 0.9014 - Recall: 0.2570 - accuracy: 0.4813 - loss: 0.9142
Epoch 29/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6574 - Precision: 0.8579 - Recall: 0.2114 - accuracy: 0.4488 - loss: 0.9891
Epoch 30/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7127 - Precision: 0.8654 - Recall: 0.2548 - accuracy: 0.5377 - loss: 0.9464
Epoch 31/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7157 - Precision: 0.8464 - Recall: 0.2268 - accuracy: 0.5453 - loss: 0.9876
Epoch 32/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7319 - Precision: 0.8589 - Recall: 0.2558 - accuracy: 0.5271 - loss: 0.9643
Epoch 33/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7589 - Precision: 0.9050 - Recall: 0.2560 - accuracy: 0.5714 - loss: 0.8730
Epoch 34/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7412 - Precision: 0.8937 - Recall: 0.2577 - accuracy: 0.5184 - loss: 0.9094
Epoch 35/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7373 - Precision: 0.8701 - Recall: 0.2410 - accuracy: 0.5514 - loss: 0.9237
Epoch 36/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7202 - Precision: 0.8398 - Recall: 0.2188 - accuracy: 0.5078 - loss: 0.9585
Epoch 37/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7270 - Precision: 0.8715 - Recall: 0.2440 - accuracy: 0.5182 - loss: 0.9274
Epoch 38/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7501 - Precision: 0.8927 - Recall: 0.2765 - accuracy: 0.5436 - loss: 0.8877
Epoch 39/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7247 - Precision: 0.8639 - Recall: 0.2523 - accuracy: 0.5121 - loss: 0.9603
Epoch 40/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7453 - Precision: 0.8938 - Recall: 0.2572 - accuracy: 0.5321 - loss: 0.8911
Epoch 41/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7422 - Precision: 0.8966 - Recall: 0.2396 - accuracy: 0.5269 - loss: 0.9127
Epoch 42/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.7280 - Precision: 0.9009 - Recall: 0.2673 - accuracy: 0.5277 - loss: 0.9074
Epoch 43/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6990 - Precision: 0.8224 - Recall: 0.2313 - accuracy: 0.4868 - loss: 0.9818
Epoch 44/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.7350 - Precision: 0.8851 - Recall: 0.2654 - accuracy: 0.5193 - loss: 0.9207
Epoch 45/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.7745 - Precision: 0.9017 - Recall: 0.2869 - accuracy: 0.5751 - loss: 0.8702
Epoch 46/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7150 - Precision: 0.8901 - Recall: 0.2495 - accuracy: 0.5010 - loss: 0.9106
Epoch 47/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.7343 - Precision: 0.9046 - Recall: 0.2634 - accuracy: 0.5332 - loss: 0.8928
Epoch 48/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6651 - Precision: 0.8566 - Recall: 0.2128 - accuracy: 0.4902 - loss: 1.1157
Epoch 49/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.7343 - Precision: 0.9151 - Recall: 0.2549 - accuracy: 0.5170 - loss: 0.8905
Epoch 50/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6846 - Precision: 0.8857 - Recall: 0.2244 - accuracy: 0.4832 - loss: 1.0451
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 44ms/step
Epoch 1/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 5s 6ms/step - AUC: 0.5336 - Precision: 0.3803 - Recall: 0.2361 - accuracy: 0.3390 - loss: 1.6265
Epoch 2/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6604 - Precision: 0.6547 - Recall: 0.2452 - accuracy: 0.4547 - loss: 1.0255
Epoch 3/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7115 - Precision: 0.7401 - Recall: 0.2730 - accuracy: 0.5224 - loss: 0.9532
Epoch 4/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7864 - Precision: 0.8475 - Recall: 0.3471 - accuracy: 0.5676 - loss: 0.8592
Epoch 5/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7928 - Precision: 0.8351 - Recall: 0.3326 - accuracy: 0.5711 - loss: 0.8335
Epoch 6/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7662 - Precision: 0.8780 - Recall: 0.3147 - accuracy: 0.5510 - loss: 0.8759
Epoch 7/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7479 - Precision: 0.8305 - Recall: 0.3062 - accuracy: 0.5255 - loss: 0.8894
Epoch 8/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7550 - Precision: 0.8712 - Recall: 0.2864 - accuracy: 0.5590 - loss: 0.8611
Epoch 9/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.7933 - Precision: 0.8630 - Recall: 0.3361 - accuracy: 0.5723 - loss: 0.8321
Epoch 10/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8082 - Precision: 0.8688 - Recall: 0.3597 - accuracy: 0.6033 - loss: 0.8068
Epoch 11/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8170 - Precision: 0.8637 - Recall: 0.3560 - accuracy: 0.5887 - loss: 0.8003
Epoch 12/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8026 - Precision: 0.9087 - Recall: 0.3519 - accuracy: 0.5966 - loss: 0.8333
Epoch 13/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8163 - Precision: 0.8762 - Recall: 0.3798 - accuracy: 0.5881 - loss: 0.7747
Epoch 14/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8360 - Precision: 0.8539 - Recall: 0.3819 - accuracy: 0.6340 - loss: 0.7837
Epoch 15/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7832 - Precision: 0.8465 - Recall: 0.3295 - accuracy: 0.5721 - loss: 0.8861
Epoch 16/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8151 - Precision: 0.8406 - Recall: 0.3516 - accuracy: 0.6060 - loss: 0.8047
Epoch 17/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7886 - Precision: 0.8936 - Recall: 0.3233 - accuracy: 0.5736 - loss: 0.8685
Epoch 18/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8306 - Precision: 0.8725 - Recall: 0.3895 - accuracy: 0.6298 - loss: 0.7976
Epoch 19/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8276 - Precision: 0.8597 - Recall: 0.3643 - accuracy: 0.6213 - loss: 0.8250
Epoch 20/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8130 - Precision: 0.8694 - Recall: 0.3696 - accuracy: 0.5946 - loss: 0.8337
Epoch 21/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8560 - Precision: 0.8697 - Recall: 0.4306 - accuracy: 0.6477 - loss: 0.7335
Epoch 22/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.7785 - Precision: 0.8440 - Recall: 0.2935 - accuracy: 0.5582 - loss: 0.9234
Epoch 23/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8112 - Precision: 0.8428 - Recall: 0.3534 - accuracy: 0.6222 - loss: 0.8467
Epoch 24/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7841 - Precision: 0.8943 - Recall: 0.3262 - accuracy: 0.5635 - loss: 0.8432
Epoch 25/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8103 - Precision: 0.8980 - Recall: 0.3270 - accuracy: 0.6209 - loss: 0.8993
Epoch 26/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7623 - Precision: 0.8773 - Recall: 0.2626 - accuracy: 0.5548 - loss: 0.8833
Epoch 27/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8143 - Precision: 0.9239 - Recall: 0.3315 - accuracy: 0.5949 - loss: 0.7743
Epoch 28/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8492 - Precision: 0.8896 - Recall: 0.3927 - accuracy: 0.6571 - loss: 0.7106
Epoch 29/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8297 - Precision: 0.8660 - Recall: 0.3750 - accuracy: 0.6312 - loss: 0.7526
Epoch 30/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8004 - Precision: 0.9126 - Recall: 0.3264 - accuracy: 0.5702 - loss: 0.8419
Epoch 31/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7935 - Precision: 0.8697 - Recall: 0.3286 - accuracy: 0.6041 - loss: 0.8622
Epoch 32/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8328 - Precision: 0.8703 - Recall: 0.3768 - accuracy: 0.6211 - loss: 0.7879
Epoch 33/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8284 - Precision: 0.8682 - Recall: 0.3997 - accuracy: 0.6139 - loss: 0.7405
Epoch 34/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8116 - Precision: 0.8851 - Recall: 0.3435 - accuracy: 0.6171 - loss: 0.8650
Epoch 35/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8270 - Precision: 0.9136 - Recall: 0.3808 - accuracy: 0.6033 - loss: 0.7562
Epoch 36/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8543 - Precision: 0.8826 - Recall: 0.4008 - accuracy: 0.6407 - loss: 0.7519
Epoch 37/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8204 - Precision: 0.9073 - Recall: 0.3541 - accuracy: 0.6038 - loss: 0.7831
Epoch 38/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8400 - Precision: 0.8779 - Recall: 0.4048 - accuracy: 0.6266 - loss: 0.7237
Epoch 39/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8032 - Precision: 0.9158 - Recall: 0.3427 - accuracy: 0.6169 - loss: 0.8007
Epoch 40/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8182 - Precision: 0.9249 - Recall: 0.3604 - accuracy: 0.6243 - loss: 0.7659
Epoch 41/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8297 - Precision: 0.9301 - Recall: 0.3423 - accuracy: 0.6124 - loss: 0.7370
Epoch 42/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8204 - Precision: 0.8786 - Recall: 0.3431 - accuracy: 0.5872 - loss: 0.8412
Epoch 43/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8249 - Precision: 0.8954 - Recall: 0.3745 - accuracy: 0.6129 - loss: 0.7966
Epoch 44/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8456 - Precision: 0.9047 - Recall: 0.3818 - accuracy: 0.6429 - loss: 0.6982
Epoch 45/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8401 - Precision: 0.8805 - Recall: 0.3889 - accuracy: 0.6292 - loss: 0.7117
Epoch 46/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8208 - Precision: 0.8714 - Recall: 0.3636 - accuracy: 0.5947 - loss: 0.8358
Epoch 47/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8292 - Precision: 0.9549 - Recall: 0.3751 - accuracy: 0.6056 - loss: 0.7547
Epoch 48/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.7952 - Precision: 0.8634 - Recall: 0.3181 - accuracy: 0.5869 - loss: 0.9262
Epoch 49/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8175 - Precision: 0.8983 - Recall: 0.3496 - accuracy: 0.6313 - loss: 0.8050
Epoch 50/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8271 - Precision: 0.9142 - Recall: 0.3878 - accuracy: 0.6146 - loss: 0.7389
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 28ms/step
Epoch 1/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 4s 7ms/step - AUC: 0.5842 - Precision: 0.4309 - Recall: 0.3231 - accuracy: 0.4325 - loss: 1.4550
Epoch 2/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.7224 - Precision: 0.6708 - Recall: 0.3226 - accuracy: 0.5167 - loss: 1.0051
Epoch 3/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7519 - Precision: 0.7415 - Recall: 0.3503 - accuracy: 0.5175 - loss: 0.9102
Epoch 4/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8034 - Precision: 0.8061 - Recall: 0.3955 - accuracy: 0.5723 - loss: 0.7954
Epoch 5/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8145 - Precision: 0.8223 - Recall: 0.3739 - accuracy: 0.5799 - loss: 0.7893
Epoch 6/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.8245 - Precision: 0.7768 - Recall: 0.4175 - accuracy: 0.5996 - loss: 0.7801
Epoch 7/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8332 - Precision: 0.7858 - Recall: 0.4285 - accuracy: 0.6371 - loss: 0.7537
Epoch 8/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8417 - Precision: 0.7660 - Recall: 0.4697 - accuracy: 0.6628 - loss: 0.7478
Epoch 9/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8387 - Precision: 0.8497 - Recall: 0.4275 - accuracy: 0.6524 - loss: 0.7421
Epoch 10/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.8285 - Precision: 0.7502 - Recall: 0.4932 - accuracy: 0.6071 - loss: 0.7599
Epoch 11/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8602 - Precision: 0.8329 - Recall: 0.4288 - accuracy: 0.6482 - loss: 0.7161
Epoch 12/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8219 - Precision: 0.7175 - Recall: 0.4626 - accuracy: 0.6072 - loss: 0.8046
Epoch 13/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.8600 - Precision: 0.7807 - Recall: 0.5348 - accuracy: 0.6932 - loss: 0.7245
Epoch 14/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8557 - Precision: 0.8917 - Recall: 0.4337 - accuracy: 0.6467 - loss: 0.7189
Epoch 15/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8614 - Precision: 0.8448 - Recall: 0.4709 - accuracy: 0.6686 - loss: 0.6958
Epoch 16/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8528 - Precision: 0.7557 - Recall: 0.4245 - accuracy: 0.6541 - loss: 0.7102
Epoch 17/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8729 - Precision: 0.8289 - Recall: 0.4509 - accuracy: 0.6595 - loss: 0.6847
Epoch 18/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.8553 - Precision: 0.7974 - Recall: 0.4455 - accuracy: 0.6399 - loss: 0.7217
Epoch 19/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.8582 - Precision: 0.8331 - Recall: 0.4581 - accuracy: 0.6849 - loss: 0.7180
Epoch 20/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8577 - Precision: 0.8410 - Recall: 0.4310 - accuracy: 0.6443 - loss: 0.6985
Epoch 21/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8747 - Precision: 0.8001 - Recall: 0.5052 - accuracy: 0.6651 - loss: 0.6686
Epoch 22/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8574 - Precision: 0.7885 - Recall: 0.4514 - accuracy: 0.6325 - loss: 0.6952
Epoch 23/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8715 - Precision: 0.8974 - Recall: 0.4182 - accuracy: 0.6640 - loss: 0.6688
Epoch 24/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.8578 - Precision: 0.7943 - Recall: 0.4574 - accuracy: 0.6393 - loss: 0.6792
Epoch 25/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8799 - Precision: 0.8763 - Recall: 0.4791 - accuracy: 0.6963 - loss: 0.6544
Epoch 26/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8685 - Precision: 0.8381 - Recall: 0.4518 - accuracy: 0.6661 - loss: 0.7055
Epoch 27/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8748 - Precision: 0.8218 - Recall: 0.4584 - accuracy: 0.6782 - loss: 0.6968
Epoch 28/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8406 - Precision: 0.8076 - Recall: 0.3976 - accuracy: 0.6087 - loss: 0.7044
Epoch 29/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8596 - Precision: 0.7949 - Recall: 0.4601 - accuracy: 0.6430 - loss: 0.6843
Epoch 30/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.8610 - Precision: 0.8391 - Recall: 0.4437 - accuracy: 0.6152 - loss: 0.6777
Epoch 31/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8521 - Precision: 0.8122 - Recall: 0.4594 - accuracy: 0.6607 - loss: 0.7468
Epoch 32/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8536 - Precision: 0.7814 - Recall: 0.4493 - accuracy: 0.6459 - loss: 0.6949
Epoch 33/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8617 - Precision: 0.8684 - Recall: 0.4353 - accuracy: 0.6333 - loss: 0.6928
Epoch 34/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8624 - Precision: 0.8118 - Recall: 0.4360 - accuracy: 0.6122 - loss: 0.6826
Epoch 35/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.8414 - Precision: 0.8163 - Recall: 0.3991 - accuracy: 0.6153 - loss: 0.7350
Epoch 36/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8809 - Precision: 0.7946 - Recall: 0.5031 - accuracy: 0.6695 - loss: 0.6310
Epoch 37/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8591 - Precision: 0.8364 - Recall: 0.4420 - accuracy: 0.6638 - loss: 0.6937
Epoch 38/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8655 - Precision: 0.8668 - Recall: 0.4471 - accuracy: 0.6591 - loss: 0.6708
Epoch 39/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8540 - Precision: 0.8146 - Recall: 0.4290 - accuracy: 0.5985 - loss: 0.6796
Epoch 40/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8716 - Precision: 0.8405 - Recall: 0.4189 - accuracy: 0.6852 - loss: 0.6511
Epoch 41/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8520 - Precision: 0.8189 - Recall: 0.3930 - accuracy: 0.6618 - loss: 0.7798
Epoch 42/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8443 - Precision: 0.8588 - Recall: 0.4150 - accuracy: 0.6414 - loss: 0.7539
Epoch 43/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8578 - Precision: 0.8012 - Recall: 0.4468 - accuracy: 0.6570 - loss: 0.6867
Epoch 44/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8092 - Precision: 0.8516 - Recall: 0.3459 - accuracy: 0.5968 - loss: 0.9417
Epoch 45/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8496 - Precision: 0.8341 - Recall: 0.4683 - accuracy: 0.6295 - loss: 0.6967
Epoch 46/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8530 - Precision: 0.8319 - Recall: 0.4065 - accuracy: 0.6643 - loss: 0.7264
Epoch 47/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8611 - Precision: 0.8800 - Recall: 0.4169 - accuracy: 0.6759 - loss: 0.8219
Epoch 48/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.8565 - Precision: 0.7642 - Recall: 0.4709 - accuracy: 0.6269 - loss: 0.6707
Epoch 49/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8427 - Precision: 0.8783 - Recall: 0.4044 - accuracy: 0.6278 - loss: 0.7333
Epoch 50/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.8492 - Precision: 0.8127 - Recall: 0.4219 - accuracy: 0.6062 - loss: 0.6853
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 35ms/step
Epoch 1/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 4s 5ms/step - AUC: 0.5839 - Precision: 0.4212 - Recall: 0.3179 - accuracy: 0.3858 - loss: 2.0556
Epoch 2/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5652 - Precision: 0.4085 - Recall: 0.1862 - accuracy: 0.4275 - loss: 1.3570
Epoch 3/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5937 - Precision: 0.4120 - Recall: 0.1332 - accuracy: 0.4491 - loss: 1.1071
Epoch 4/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5772 - Precision: 0.4289 - Recall: 0.1111 - accuracy: 0.4299 - loss: 1.1137
Epoch 5/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6505 - Precision: 0.5733 - Recall: 0.2137 - accuracy: 0.5294 - loss: 1.0657
Epoch 6/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6383 - Precision: 0.5439 - Recall: 0.1937 - accuracy: 0.5240 - loss: 1.0684
Epoch 7/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6021 - Precision: 0.5074 - Recall: 0.1007 - accuracy: 0.4629 - loss: 1.1204
Epoch 8/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5995 - Precision: 0.4716 - Recall: 0.1127 - accuracy: 0.4616 - loss: 1.0737
Epoch 9/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6140 - Precision: 0.4423 - Recall: 0.0683 - accuracy: 0.4857 - loss: 1.0752
Epoch 10/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6156 - Precision: 0.4833 - Recall: 0.3451 - accuracy: 0.4689 - loss: 1.0810
Epoch 11/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5995 - Precision: 0.4381 - Recall: 0.3241 - accuracy: 0.4944 - loss: 1.0604
Epoch 12/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6249 - Precision: 0.4790 - Recall: 0.0653 - accuracy: 0.5014 - loss: 1.0569
Epoch 13/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6169 - Precision: 0.4984 - Recall: 0.0948 - accuracy: 0.4862 - loss: 1.0557
Epoch 14/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5915 - Precision: 0.3865 - Recall: 0.1101 - accuracy: 0.4593 - loss: 1.0943
Epoch 15/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6446 - Precision: 0.5374 - Recall: 0.5068 - accuracy: 0.5325 - loss: 1.0238
Epoch 16/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5993 - Precision: 0.2670 - Recall: 0.0067 - accuracy: 0.4827 - loss: 1.0632
Epoch 17/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6298 - Precision: 0.4821 - Recall: 0.3703 - accuracy: 0.5228 - loss: 1.0280
Epoch 18/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6258 - Precision: 0.4948 - Recall: 0.0347 - accuracy: 0.5169 - loss: 1.0322
Epoch 19/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6343 - Precision: 0.5031 - Recall: 0.1166 - accuracy: 0.5171 - loss: 1.0452
Epoch 20/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6249 - Precision: 0.4008 - Recall: 0.0259 - accuracy: 0.5079 - loss: 1.0363
Epoch 21/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6072 - Precision: 0.0820 - Recall: 0.0070 - accuracy: 0.4917 - loss: 1.0489   1
Epoch 22/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6317 - Precision: 0.4494 - Recall: 0.2947 - accuracy: 0.5073 - loss: 1.0346
Epoch 23/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5954 - Precision: 0.1890 - Recall: 0.0271 - accuracy: 0.4916 - loss: 1.0480
Epoch 24/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 3ms/step - AUC: 0.5990 - Precision: 0.2703 - Recall: 0.0561 - accuracy: 0.4657 - loss: 1.0698
Epoch 25/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6125 - Precision: 0.4066 - Recall: 0.1348 - accuracy: 0.4861 - loss: 1.0841
Epoch 26/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6027 - Precision: 0.4739 - Recall: 0.2620 - accuracy: 0.4892 - loss: 1.0537
Epoch 27/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5957 - Precision: 0.1830 - Recall: 0.0245 - accuracy: 0.4901 - loss: 1.0483
Epoch 28/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.5911 - Precision: 0.0770 - Recall: 0.0019 - accuracy: 0.4819 - loss: 1.0520
Epoch 29/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6152 - Precision: 0.3472 - Recall: 0.1140 - accuracy: 0.4888 - loss: 1.0499
Epoch 30/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6122 - Precision: 0.1342 - Recall: 0.0054 - accuracy: 0.4935 - loss: 1.0451
Epoch 31/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6450 - Precision: 0.5505 - Recall: 0.5364 - accuracy: 0.5487 - loss: 1.0056
Epoch 32/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5931 - Precision: 0.0127 - Recall: 2.0303e-04 - accuracy: 0.4698 - loss: 1.0606   
Epoch 33/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6511 - Precision: 0.5491 - Recall: 0.5199 - accuracy: 0.5505 - loss: 1.0044
Epoch 34/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6288 - Precision: 0.3210 - Recall: 0.1236 - accuracy: 0.5153 - loss: 1.0331
Epoch 35/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6151 - Precision: 0.2711 - Recall: 0.0749 - accuracy: 0.4808 - loss: 1.0518
Epoch 36/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6248 - Precision: 0.4252 - Recall: 0.0654 - accuracy: 0.4884 - loss: 1.0515
Epoch 37/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5966 - Precision: 0.3400 - Recall: 0.0952 - accuracy: 0.4979 - loss: 1.0428
Epoch 38/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6147 - Precision: 0.5334 - Recall: 0.0303 - accuracy: 0.4808 - loss: 1.0944
Epoch 39/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6201 - Precision: 0.5155 - Recall: 0.4812 - accuracy: 0.5162 - loss: 1.0907
Epoch 40/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6291 - Precision: 0.3831 - Recall: 0.1226 - accuracy: 0.5094 - loss: 1.0337
Epoch 41/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6002 - Precision: 0.0469 - Recall: 0.0022 - accuracy: 0.4817 - loss: 1.0933     
Epoch 42/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6107 - Precision: 0.5014 - Recall: 0.3669 - accuracy: 0.4966 - loss: 1.0453
Epoch 43/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6034 - Precision: 0.4588 - Recall: 0.2723 - accuracy: 0.4855 - loss: 1.0556
Epoch 44/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6239 - Precision: 0.5053 - Recall: 0.4736 - accuracy: 0.5032 - loss: 1.0372
Epoch 45/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6252 - Precision: 0.4129 - Recall: 0.1637 - accuracy: 0.5056 - loss: 1.0377
Epoch 46/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6027 - Precision: 0.4061 - Recall: 0.1370 - accuracy: 0.4811 - loss: 1.0542
Epoch 47/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5967 - Precision: 0.3334 - Recall: 0.0504 - accuracy: 0.4673 - loss: 1.0629
Epoch 48/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6017 - Precision: 0.4612 - Recall: 0.2141 - accuracy: 0.4744 - loss: 1.0581
Epoch 49/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6156 - Precision: 0.4869 - Recall: 0.3781 - accuracy: 0.5026 - loss: 1.0402
Epoch 50/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6101 - Precision: 0.4103 - Recall: 0.1920 - accuracy: 0.4898 - loss: 1.0466
5/5 ━━━━━━━━━━━━━━━━━━━━ 1s 70ms/step
Epoch 1/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 4s 5ms/step - AUC: 0.5450 - Precision: 0.3745 - Recall: 0.3094 - accuracy: 0.3538 - loss: 2.7938
Epoch 2/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5724 - Precision: 0.4117 - Recall: 0.2481 - accuracy: 0.4175 - loss: 1.5314
Epoch 3/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5620 - Precision: 0.4389 - Recall: 0.1760 - accuracy: 0.4415 - loss: 1.3026
Epoch 4/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5936 - Precision: 0.4621 - Recall: 0.1440 - accuracy: 0.4497 - loss: 1.1380
Epoch 5/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5886 - Precision: 0.4857 - Recall: 0.1343 - accuracy: 0.4407 - loss: 1.1292
Epoch 6/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6223 - Precision: 0.4759 - Recall: 0.1338 - accuracy: 0.5115 - loss: 1.0700
Epoch 7/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6102 - Precision: 0.5291 - Recall: 0.1046 - accuracy: 0.4717 - loss: 1.0843
Epoch 8/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6218 - Precision: 0.5341 - Recall: 0.1196 - accuracy: 0.4621 - loss: 1.0571
Epoch 9/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6329 - Precision: 0.5479 - Recall: 0.1559 - accuracy: 0.5001 - loss: 1.0565
Epoch 10/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5932 - Precision: 0.4921 - Recall: 0.0985 - accuracy: 0.4605 - loss: 1.0685
Epoch 11/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6324 - Precision: 0.5656 - Recall: 0.1559 - accuracy: 0.4975 - loss: 1.0574
Epoch 12/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6511 - Precision: 0.6367 - Recall: 0.1434 - accuracy: 0.4957 - loss: 1.0378
Epoch 13/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6280 - Precision: 0.6363 - Recall: 0.1686 - accuracy: 0.4493 - loss: 1.0662
Epoch 14/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6853 - Precision: 0.7667 - Recall: 0.1975 - accuracy: 0.5149 - loss: 1.0024
Epoch 15/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6522 - Precision: 0.6513 - Recall: 0.1729 - accuracy: 0.4788 - loss: 1.0093
Epoch 16/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6679 - Precision: 0.6908 - Recall: 0.1913 - accuracy: 0.5128 - loss: 1.0634
Epoch 17/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6894 - Precision: 0.7023 - Recall: 0.1829 - accuracy: 0.5140 - loss: 1.0277
Epoch 18/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6729 - Precision: 0.7142 - Recall: 0.2068 - accuracy: 0.4835 - loss: 0.9968
Epoch 19/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7070 - Precision: 0.8403 - Recall: 0.2459 - accuracy: 0.5115 - loss: 0.9118
Epoch 20/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6907 - Precision: 0.8299 - Recall: 0.2020 - accuracy: 0.4911 - loss: 0.9731
Epoch 21/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6511 - Precision: 0.7087 - Recall: 0.1857 - accuracy: 0.4749 - loss: 1.0320
Epoch 22/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7051 - Precision: 0.7678 - Recall: 0.2149 - accuracy: 0.5190 - loss: 0.9738
Epoch 23/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7012 - Precision: 0.7969 - Recall: 0.1949 - accuracy: 0.5247 - loss: 0.9959
Epoch 24/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6545 - Precision: 0.7660 - Recall: 0.1851 - accuracy: 0.4778 - loss: 1.0509
Epoch 25/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7104 - Precision: 0.8555 - Recall: 0.2096 - accuracy: 0.5151 - loss: 0.9554
Epoch 26/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6030 - Precision: 0.5485 - Recall: 0.1245 - accuracy: 0.4458 - loss: 1.1556
Epoch 27/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6721 - Precision: 0.8047 - Recall: 0.1949 - accuracy: 0.4793 - loss: 1.0902
Epoch 28/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6723 - Precision: 0.7315 - Recall: 0.1774 - accuracy: 0.5053 - loss: 0.9808
Epoch 29/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6666 - Precision: 0.7524 - Recall: 0.1522 - accuracy: 0.4894 - loss: 1.0101
Epoch 30/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6600 - Precision: 0.8035 - Recall: 0.1632 - accuracy: 0.4886 - loss: 1.0600
Epoch 31/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6419 - Precision: 0.8082 - Recall: 0.1150 - accuracy: 0.4726 - loss: 1.0099
Epoch 32/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6343 - Precision: 0.7457 - Recall: 0.1422 - accuracy: 0.4735 - loss: 1.0501
Epoch 33/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6595 - Precision: 0.7434 - Recall: 0.1492 - accuracy: 0.4913 - loss: 1.0158
Epoch 34/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6477 - Precision: 0.7765 - Recall: 0.1589 - accuracy: 0.4845 - loss: 1.0078
Epoch 35/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6443 - Precision: 0.6687 - Recall: 0.1344 - accuracy: 0.4865 - loss: 1.1581
Epoch 36/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6224 - Precision: 0.6551 - Recall: 0.1027 - accuracy: 0.4695 - loss: 1.1966
Epoch 37/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6705 - Precision: 0.7822 - Recall: 0.1531 - accuracy: 0.5029 - loss: 1.0107
Epoch 38/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 9ms/step - AUC: 0.6406 - Precision: 0.7851 - Recall: 0.1122 - accuracy: 0.4675 - loss: 1.0530
Epoch 39/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6693 - Precision: 0.7882 - Recall: 0.1460 - accuracy: 0.5001 - loss: 1.0315
Epoch 40/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6331 - Precision: 0.7154 - Recall: 0.1067 - accuracy: 0.4801 - loss: 1.0392
Epoch 41/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6327 - Precision: 0.6480 - Recall: 0.1145 - accuracy: 0.4798 - loss: 1.0494
Epoch 42/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6262 - Precision: 0.7210 - Recall: 0.0979 - accuracy: 0.4641 - loss: 1.0504
Epoch 43/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6417 - Precision: 0.7188 - Recall: 0.0770 - accuracy: 0.4897 - loss: 1.0732
Epoch 44/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6068 - Precision: 0.7649 - Recall: 0.0371 - accuracy: 0.4661 - loss: 1.0586
Epoch 45/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6300 - Precision: 0.7658 - Recall: 0.0578 - accuracy: 0.4802 - loss: 1.0355
Epoch 46/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6508 - Precision: 0.8532 - Recall: 0.1032 - accuracy: 0.5000 - loss: 1.0233
Epoch 47/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.7016 - Precision: 0.8517 - Recall: 0.1205 - accuracy: 0.5465 - loss: 0.9928
Epoch 48/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6076 - Precision: 0.7586 - Recall: 0.0827 - accuracy: 0.4683 - loss: 1.0580
Epoch 49/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6214 - Precision: 0.6964 - Recall: 0.0973 - accuracy: 0.4661 - loss: 1.0961
Epoch 50/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6504 - Precision: 0.8386 - Recall: 0.1023 - accuracy: 0.4953 - loss: 1.0150
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 37ms/step
Epoch 1/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 17s 6ms/step - AUC: 0.5035 - Precision: 0.3359 - Recall: 0.2779 - accuracy: 0.3432 - loss: 3.4301
Epoch 2/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.5537 - Precision: 0.3910 - Recall: 0.2338 - accuracy: 0.4191 - loss: 1.5824
Epoch 3/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6046 - Precision: 0.4429 - Recall: 0.1864 - accuracy: 0.4316 - loss: 1.2116
Epoch 4/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6123 - Precision: 0.4882 - Recall: 0.2138 - accuracy: 0.4544 - loss: 1.1584
Epoch 5/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5929 - Precision: 0.5196 - Recall: 0.1439 - accuracy: 0.4372 - loss: 1.1115
Epoch 6/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5796 - Precision: 0.4134 - Recall: 0.1104 - accuracy: 0.4428 - loss: 1.1275
Epoch 7/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6046 - Precision: 0.4710 - Recall: 0.1689 - accuracy: 0.4579 - loss: 1.1010
Epoch 8/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6351 - Precision: 0.5656 - Recall: 0.2196 - accuracy: 0.4960 - loss: 1.0858
Epoch 9/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6619 - Precision: 0.6371 - Recall: 0.1780 - accuracy: 0.5127 - loss: 1.0237
Epoch 10/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6223 - Precision: 0.5293 - Recall: 0.1568 - accuracy: 0.4782 - loss: 1.0585
Epoch 11/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6588 - Precision: 0.5534 - Recall: 0.1607 - accuracy: 0.4912 - loss: 1.0411
Epoch 12/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6302 - Precision: 0.5889 - Recall: 0.1256 - accuracy: 0.4976 - loss: 1.0352
Epoch 13/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6440 - Precision: 0.6396 - Recall: 0.1411 - accuracy: 0.4782 - loss: 1.0266 
Epoch 14/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6727 - Precision: 0.7039 - Recall: 0.2247 - accuracy: 0.5290 - loss: 1.0249
Epoch 15/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6931 - Precision: 0.7344 - Recall: 0.1960 - accuracy: 0.5230 - loss: 0.9931
Epoch 16/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6333 - Precision: 0.6276 - Recall: 0.1662 - accuracy: 0.4712 - loss: 1.0297
Epoch 17/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6634 - Precision: 0.6313 - Recall: 0.1610 - accuracy: 0.4968 - loss: 1.0162
Epoch 18/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6605 - Precision: 0.7180 - Recall: 0.2100 - accuracy: 0.4664 - loss: 1.0464
Epoch 19/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6378 - Precision: 0.6474 - Recall: 0.1706 - accuracy: 0.4580 - loss: 1.0497
Epoch 20/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.7042 - Precision: 0.7276 - Recall: 0.2280 - accuracy: 0.5127 - loss: 0.9618
Epoch 21/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6187 - Precision: 0.6450 - Recall: 0.1371 - accuracy: 0.4108 - loss: 1.0344
Epoch 22/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.7073 - Precision: 0.7172 - Recall: 0.2653 - accuracy: 0.5200 - loss: 0.9699
Epoch 23/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6850 - Precision: 0.7650 - Recall: 0.2216 - accuracy: 0.5001 - loss: 0.9714
Epoch 24/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.7129 - Precision: 0.8380 - Recall: 0.2519 - accuracy: 0.4956 - loss: 0.9281
Epoch 25/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6598 - Precision: 0.7240 - Recall: 0.1749 - accuracy: 0.4768 - loss: 1.0909
Epoch 26/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7149 - Precision: 0.8541 - Recall: 0.2645 - accuracy: 0.5118 - loss: 0.9302
Epoch 27/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7182 - Precision: 0.7756 - Recall: 0.2571 - accuracy: 0.5168 - loss: 0.9680
Epoch 28/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.7246 - Precision: 0.8172 - Recall: 0.2695 - accuracy: 0.4998 - loss: 0.9540
Epoch 29/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7028 - Precision: 0.8121 - Recall: 0.2540 - accuracy: 0.4839 - loss: 0.9046
Epoch 30/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6967 - Precision: 0.7972 - Recall: 0.2480 - accuracy: 0.4784 - loss: 0.9447
Epoch 31/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6924 - Precision: 0.8480 - Recall: 0.2529 - accuracy: 0.4659 - loss: 0.9559
Epoch 32/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6737 - Precision: 0.7964 - Recall: 0.1862 - accuracy: 0.4693 - loss: 0.9772
Epoch 33/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7096 - Precision: 0.8059 - Recall: 0.2429 - accuracy: 0.5066 - loss: 0.9375
Epoch 34/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6899 - Precision: 0.8206 - Recall: 0.1959 - accuracy: 0.4961 - loss: 0.9524
Epoch 35/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.7099 - Precision: 0.8441 - Recall: 0.2465 - accuracy: 0.5100 - loss: 0.9785
Epoch 36/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7088 - Precision: 0.8357 - Recall: 0.2409 - accuracy: 0.4745 - loss: 0.9462
Epoch 37/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7073 - Precision: 0.9398 - Recall: 0.2179 - accuracy: 0.4893 - loss: 0.9019
Epoch 38/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.7206 - Precision: 0.8992 - Recall: 0.2434 - accuracy: 0.5164 - loss: 0.9079
Epoch 39/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7180 - Precision: 0.8767 - Recall: 0.2419 - accuracy: 0.5072 - loss: 0.8922
Epoch 40/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6994 - Precision: 0.8883 - Recall: 0.2472 - accuracy: 0.5074 - loss: 0.9589
Epoch 41/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.7194 - Precision: 0.8697 - Recall: 0.2732 - accuracy: 0.4966 - loss: 0.9675
Epoch 42/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6912 - Precision: 0.8931 - Recall: 0.2675 - accuracy: 0.4818 - loss: 0.9612
Epoch 43/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.7011 - Precision: 0.8455 - Recall: 0.2292 - accuracy: 0.4799 - loss: 0.9075
Epoch 44/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6755 - Precision: 0.8260 - Recall: 0.2243 - accuracy: 0.4578 - loss: 0.9547
Epoch 45/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7198 - Precision: 0.9160 - Recall: 0.2671 - accuracy: 0.4834 - loss: 0.8587
Epoch 46/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6873 - Precision: 0.8874 - Recall: 0.2189 - accuracy: 0.4856 - loss: 1.0424
Epoch 47/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.7142 - Precision: 0.9098 - Recall: 0.2520 - accuracy: 0.4998 - loss: 0.9257
Epoch 48/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.7094 - Precision: 0.9045 - Recall: 0.2484 - accuracy: 0.5072 - loss: 0.8910
Epoch 49/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.7117 - Precision: 0.9685 - Recall: 0.2711 - accuracy: 0.4679 - loss: 0.8523
Epoch 50/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.7224 - Precision: 0.9505 - Recall: 0.2384 - accuracy: 0.5271 - loss: 0.9340
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 33ms/step
Epoch 1/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 7s 6ms/step - AUC: 0.5442 - Precision: 0.4525 - Recall: 0.2025 - accuracy: 0.3772 - loss: 3.4163
Epoch 2/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6046 - Precision: 0.4660 - Recall: 0.2133 - accuracy: 0.5021 - loss: 1.0672
Epoch 3/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6198 - Precision: 0.4341 - Recall: 0.1927 - accuracy: 0.5050 - loss: 1.0885
Epoch 4/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6446 - Precision: 0.4584 - Recall: 0.2154 - accuracy: 0.5107 - loss: 1.0384
Epoch 5/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6478 - Precision: 0.4895 - Recall: 0.2481 - accuracy: 0.5092 - loss: 1.0401
Epoch 6/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6062 - Precision: 0.3978 - Recall: 0.0994 - accuracy: 0.4797 - loss: 1.0633
Epoch 7/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.5990 - Precision: 0.3690 - Recall: 0.1638 - accuracy: 0.4369 - loss: 1.0774
Epoch 8/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5916 - Precision: 0.3688 - Recall: 0.0999 - accuracy: 0.4782 - loss: 1.0741
Epoch 9/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6330 - Precision: 0.5369 - Recall: 0.3201 - accuracy: 0.5054 - loss: 1.0532
Epoch 10/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6046 - Precision: 0.4212 - Recall: 0.2286 - accuracy: 0.5124 - loss: 1.0560
Epoch 11/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6241 - Precision: 0.4123 - Recall: 0.2181 - accuracy: 0.5037 - loss: 1.0489
Epoch 12/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5977 - Precision: 0.3765 - Recall: 0.1350 - accuracy: 0.4481 - loss: 1.0764
Epoch 13/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5972 - Precision: 0.4067 - Recall: 0.1146 - accuracy: 0.4833 - loss: 1.0866
Epoch 14/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5928 - Precision: 0.4726 - Recall: 0.2418 - accuracy: 0.4862 - loss: 1.9670
Epoch 15/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.5809 - Precision: 0.3844 - Recall: 0.1311 - accuracy: 0.4532 - loss: 1.0914
Epoch 16/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6069 - Precision: 0.4612 - Recall: 0.2192 - accuracy: 0.4905 - loss: 1.0642
Epoch 17/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6070 - Precision: 0.4190 - Recall: 0.1489 - accuracy: 0.4869 - loss: 1.0721
Epoch 18/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5946 - Precision: 0.4772 - Recall: 0.2892 - accuracy: 0.4752 - loss: 1.5422
Epoch 19/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6143 - Precision: 0.4226 - Recall: 0.1938 - accuracy: 0.4790 - loss: 1.0751
Epoch 20/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5899 - Precision: 0.4694 - Recall: 0.2052 - accuracy: 0.4817 - loss: 1.0684
Epoch 21/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6332 - Precision: 0.5341 - Recall: 0.3745 - accuracy: 0.5266 - loss: 1.0472
Epoch 22/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6209 - Precision: 0.4184 - Recall: 0.2132 - accuracy: 0.5287 - loss: 3.4494
Epoch 23/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6099 - Precision: 0.4282 - Recall: 0.1954 - accuracy: 0.4839 - loss: 1.0643
Epoch 24/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6279 - Precision: 0.4918 - Recall: 0.2248 - accuracy: 0.5151 - loss: 1.2806
Epoch 25/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6163 - Precision: 0.4872 - Recall: 0.1491 - accuracy: 0.4870 - loss: 1.0762
Epoch 26/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6087 - Precision: 0.4877 - Recall: 0.2508 - accuracy: 0.5067 - loss: 1.0484
Epoch 27/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6132 - Precision: 0.4034 - Recall: 0.1779 - accuracy: 0.4933 - loss: 1.0625
Epoch 28/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5849 - Precision: 0.3686 - Recall: 0.1174 - accuracy: 0.4259 - loss: 1.0803
Epoch 29/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5672 - Precision: 0.4154 - Recall: 0.1999 - accuracy: 0.4539 - loss: 1.1273
Epoch 30/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5865 - Precision: 0.4638 - Recall: 0.2595 - accuracy: 0.4327 - loss: 1.0971
Epoch 31/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6038 - Precision: 0.4811 - Recall: 0.2602 - accuracy: 0.4894 - loss: 1.0656
Epoch 32/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6177 - Precision: 0.5062 - Recall: 0.3371 - accuracy: 0.5080 - loss: 1.0529
Epoch 33/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6040 - Precision: 0.2191 - Recall: 0.0354 - accuracy: 0.4897 - loss: 1.0560
Epoch 34/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6379 - Precision: 0.5408 - Recall: 0.4135 - accuracy: 0.5285 - loss: 1.0341
Epoch 35/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6356 - Precision: 0.4598 - Recall: 0.1896 - accuracy: 0.4954 - loss: 1.0496
Epoch 36/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6330 - Precision: 0.4837 - Recall: 0.2768 - accuracy: 0.5307 - loss: 1.0424
Epoch 37/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6162 - Precision: 0.4279 - Recall: 0.1784 - accuracy: 0.4977 - loss: 1.0561
Epoch 38/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5870 - Precision: 0.3134 - Recall: 0.0861 - accuracy: 0.4707 - loss: 1.0709
Epoch 39/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6173 - Precision: 0.4944 - Recall: 0.2568 - accuracy: 0.5024 - loss: 1.0676
Epoch 40/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6367 - Precision: 0.5047 - Recall: 0.3252 - accuracy: 0.5119 - loss: 1.0441
Epoch 41/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.5895 - Precision: 0.3839 - Recall: 0.1817 - accuracy: 0.4873 - loss: 1.0622
Epoch 42/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6125 - Precision: 0.5159 - Recall: 0.3910 - accuracy: 0.5023 - loss: 1.0535
Epoch 43/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6089 - Precision: 0.4698 - Recall: 0.3013 - accuracy: 0.4954 - loss: 1.0685
Epoch 44/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6010 - Precision: 0.4802 - Recall: 0.2779 - accuracy: 0.4867 - loss: 1.0605
Epoch 45/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6150 - Precision: 0.4896 - Recall: 0.2387 - accuracy: 0.5018 - loss: 1.0561
Epoch 46/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6224 - Precision: 0.4492 - Recall: 0.1894 - accuracy: 0.4995 - loss: 1.0495
Epoch 47/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6074 - Precision: 0.3835 - Recall: 0.1241 - accuracy: 0.4829 - loss: 1.0618
Epoch 48/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6087 - Precision: 0.4034 - Recall: 0.1721 - accuracy: 0.5045 - loss: 1.0559
Epoch 49/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6075 - Precision: 0.4157 - Recall: 0.1177 - accuracy: 0.4871 - loss: 1.0593
Epoch 50/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6081 - Precision: 0.3999 - Recall: 0.1520 - accuracy: 0.4875 - loss: 1.0580
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 27ms/step
Epoch 1/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 5s 6ms/step - AUC: 0.5321 - Precision: 0.3573 - Recall: 0.1871 - accuracy: 0.3650 - loss: 2.5484
Epoch 2/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5875 - Precision: 0.4240 - Recall: 0.1648 - accuracy: 0.4708 - loss: 1.1224
Epoch 3/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5853 - Precision: 0.4637 - Recall: 0.2370 - accuracy: 0.4778 - loss: 1.1239
Epoch 4/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6160 - Precision: 0.4537 - Recall: 0.2940 - accuracy: 0.5068 - loss: 1.0820
Epoch 5/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5906 - Precision: 0.3453 - Recall: 0.1581 - accuracy: 0.4832 - loss: 1.0711
Epoch 6/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6191 - Precision: 0.2262 - Recall: 0.0555 - accuracy: 0.4985 - loss: 1.0531
Epoch 7/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6403 - Precision: 0.4197 - Recall: 0.1701 - accuracy: 0.5145 - loss: 1.0446
Epoch 8/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6003 - Precision: 0.5134 - Recall: 0.3313 - accuracy: 0.4981 - loss: 1.0495
Epoch 9/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6172 - Precision: 0.4975 - Recall: 0.2805 - accuracy: 0.4983 - loss: 1.0639
Epoch 10/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6429 - Precision: 0.5176 - Recall: 0.3864 - accuracy: 0.5157 - loss: 1.0328
Epoch 11/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6007 - Precision: 0.4728 - Recall: 0.2904 - accuracy: 0.4828 - loss: 1.0768
Epoch 12/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6226 - Precision: 0.4214 - Recall: 0.2236 - accuracy: 0.4931 - loss: 1.0531
Epoch 13/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6007 - Precision: 0.4840 - Recall: 0.2312 - accuracy: 0.4922 - loss: 1.0592
Epoch 14/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6242 - Precision: 0.4765 - Recall: 0.2938 - accuracy: 0.5099 - loss: 1.0385
Epoch 15/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5996 - Precision: 0.3783 - Recall: 0.1288 - accuracy: 0.4654 - loss: 1.0740
Epoch 16/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5981 - Precision: 0.2999 - Recall: 0.0960 - accuracy: 0.4644 - loss: 1.0697
Epoch 17/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5625 - Precision: 0.2620 - Recall: 0.0456 - accuracy: 0.4564 - loss: 1.0889
Epoch 18/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5976 - Precision: 0.4745 - Recall: 0.2608 - accuracy: 0.4768 - loss: 1.0796
Epoch 19/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6345 - Precision: 0.5213 - Recall: 0.4809 - accuracy: 0.5162 - loss: 1.0425
Epoch 20/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6228 - Precision: 0.3623 - Recall: 0.1420 - accuracy: 0.5053 - loss: 1.0742
Epoch 21/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6380 - Precision: 0.4662 - Recall: 0.2768 - accuracy: 0.5225 - loss: 1.0439
Epoch 22/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5864 - Precision: 0.2928 - Recall: 0.0923 - accuracy: 0.4609 - loss: 1.0717
Epoch 23/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6109 - Precision: 0.5015 - Recall: 0.2499 - accuracy: 0.4905 - loss: 1.0496
Epoch 24/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5829 - Precision: 0.4445 - Recall: 0.2725 - accuracy: 0.4683 - loss: 1.0871
Epoch 25/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6419 - Precision: 0.5313 - Recall: 0.4133 - accuracy: 0.5231 - loss: 1.0260
Epoch 26/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6415 - Precision: 0.4528 - Recall: 0.2083 - accuracy: 0.5321 - loss: 1.0355
Epoch 27/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6130 - Precision: 0.3348 - Recall: 0.1432 - accuracy: 0.4901 - loss: 1.0495
Epoch 28/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6078 - Precision: 0.3566 - Recall: 0.1353 - accuracy: 0.4843 - loss: 1.0606
Epoch 29/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6149 - Precision: 0.4368 - Recall: 0.2285 - accuracy: 0.4781 - loss: 1.0668
Epoch 30/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5830 - Precision: 0.4475 - Recall: 0.2507 - accuracy: 0.4743 - loss: 1.1057
Epoch 31/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5919 - Precision: 0.4525 - Recall: 0.2432 - accuracy: 0.4748 - loss: 1.0719
Epoch 32/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5975 - Precision: 0.4725 - Recall: 0.2213 - accuracy: 0.4799 - loss: 1.0674
Epoch 33/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6158 - Precision: 0.4522 - Recall: 0.2133 - accuracy: 0.4942 - loss: 1.0553
Epoch 34/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6166 - Precision: 0.4977 - Recall: 0.4263 - accuracy: 0.5027 - loss: 1.0476
Epoch 35/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6011 - Precision: 0.4642 - Recall: 0.2993 - accuracy: 0.4983 - loss: 1.1076
Epoch 36/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5811 - Precision: 0.3424 - Recall: 0.1363 - accuracy: 0.4761 - loss: 1.0683
Epoch 37/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6038 - Precision: 0.4689 - Recall: 0.2162 - accuracy: 0.4780 - loss: 1.0602
Epoch 38/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6009 - Precision: 0.4579 - Recall: 0.2612 - accuracy: 0.4783 - loss: 1.0651
Epoch 39/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6481 - Precision: 0.5353 - Recall: 0.4279 - accuracy: 0.5283 - loss: 1.0252
Epoch 40/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6067 - Precision: 0.4770 - Recall: 0.3620 - accuracy: 0.4957 - loss: 1.0517
Epoch 41/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6044 - Precision: 0.1541 - Recall: 0.0231 - accuracy: 0.4722 - loss: 1.0623
Epoch 42/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6137 - Precision: 0.4380 - Recall: 0.1737 - accuracy: 0.4931 - loss: 1.0553
Epoch 43/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6085 - Precision: 0.3778 - Recall: 0.1464 - accuracy: 0.5132 - loss: 1.0450
Epoch 44/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6139 - Precision: 0.3388 - Recall: 0.1248 - accuracy: 0.4724 - loss: 1.0644
Epoch 45/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6494 - Precision: 0.5026 - Recall: 0.4103 - accuracy: 0.5358 - loss: 1.0168
Epoch 46/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6120 - Precision: 0.2588 - Recall: 0.0573 - accuracy: 0.4937 - loss: 1.0594
Epoch 47/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 9ms/step - AUC: 0.6009 - Precision: 0.5496 - Recall: 0.1429 - accuracy: 0.4999 - loss: 1.0547
Epoch 48/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.5948 - Precision: 0.3256 - Recall: 0.0909 - accuracy: 0.4861 - loss: 1.0699
Epoch 49/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6170 - Precision: 0.3996 - Recall: 0.1902 - accuracy: 0.5010 - loss: 1.0540
Epoch 50/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 9ms/step - AUC: 0.5852 - Precision: 0.4753 - Recall: 0.3453 - accuracy: 0.4789 - loss: 1.0729
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 53ms/step
Epoch 1/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 5s 6ms/step - AUC: 0.5992 - Precision: 0.4878 - Recall: 0.3126 - accuracy: 0.4138 - loss: 2.1886
Epoch 2/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6259 - Precision: 0.5316 - Recall: 0.1817 - accuracy: 0.4867 - loss: 1.6743
Epoch 3/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6317 - Precision: 0.4289 - Recall: 0.1205 - accuracy: 0.5137 - loss: 1.1174
Epoch 4/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6237 - Precision: 0.4280 - Recall: 0.0991 - accuracy: 0.4998 - loss: 1.0596   
Epoch 5/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6077 - Precision: 0.7231 - Recall: 0.0515 - accuracy: 0.4625 - loss: 1.0640   
Epoch 6/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6167 - Precision: 0.4778 - Recall: 0.1791 - accuracy: 0.4868 - loss: 1.1496
Epoch 7/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6151 - Precision: 0.4761 - Recall: 0.2651 - accuracy: 0.4774 - loss: 1.4066
Epoch 8/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5978 - Precision: 0.4707 - Recall: 0.3536 - accuracy: 0.4828 - loss: 1.0694
Epoch 9/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5933 - Precision: 0.4442 - Recall: 0.1819 - accuracy: 0.4962 - loss: 1.0693
Epoch 10/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6172 - Precision: 0.4045 - Recall: 0.2128 - accuracy: 0.5180 - loss: 1.0428
Epoch 11/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5833 - Precision: 0.0704 - Recall: 0.0051 - accuracy: 0.4783 - loss: 1.0685    
Epoch 12/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5936 - Precision: 0.4606 - Recall: 0.3460 - accuracy: 0.4756 - loss: 1.0749
Epoch 13/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6182 - Precision: 0.0605 - Recall: 0.0032 - accuracy: 0.5051 - loss: 1.0424        
Epoch 14/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6194 - Precision: 0.5018 - Recall: 0.3404 - accuracy: 0.5039 - loss: 1.0426
Epoch 15/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5921 - Precision: 0.3906 - Recall: 0.1468 - accuracy: 0.4841 - loss: 1.0586   
Epoch 16/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6025 - Precision: 0.2821 - Recall: 0.1036 - accuracy: 0.4913 - loss: 1.0496   
Epoch 17/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6108 - Precision: 0.2184 - Recall: 0.0605 - accuracy: 0.4862 - loss: 1.0592    
Epoch 18/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5710 - Precision: 0.2357 - Recall: 0.0736 - accuracy: 0.4607 - loss: 1.0820     
Epoch 19/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6100 - Precision: 0.5056 - Recall: 0.4611 - accuracy: 0.5058 - loss: 1.0410
Epoch 20/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6281 - Precision: 0.3024 - Recall: 0.1145 - accuracy: 0.4953 - loss: 1.0495   
Epoch 21/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5932 - Precision: 0.2682 - Recall: 0.0848 - accuracy: 0.4697 - loss: 1.0741     
Epoch 22/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6076 - Precision: 0.4708 - Recall: 0.2615 - accuracy: 0.4992 - loss: 1.0497
Epoch 23/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6208 - Precision: 0.3117 - Recall: 0.1206 - accuracy: 0.4993 - loss: 1.0422    
Epoch 24/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6021 - Precision: 0.2902 - Recall: 0.0959 - accuracy: 0.4217 - loss: 1.0682
Epoch 25/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6085 - Precision: 0.4436 - Recall: 0.2590 - accuracy: 0.4844 - loss: 1.0544  
Epoch 26/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6105 - Precision: 0.4656 - Recall: 0.2269 - accuracy: 0.4890 - loss: 1.0532
Epoch 27/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5905 - Precision: 0.4650 - Recall: 0.2346 - accuracy: 0.4880 - loss: 1.0555
Epoch 28/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5856 - Precision: 0.4584 - Recall: 0.2570 - accuracy: 0.4763 - loss: 1.0640
Epoch 29/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6060 - Precision: 0.4811 - Recall: 0.2158 - accuracy: 0.4934 - loss: 1.0550
Epoch 30/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6211 - Precision: 0.3611 - Recall: 0.0784 - accuracy: 0.4956 - loss: 1.0501
Epoch 31/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6034 - Precision: 0.4172 - Recall: 0.1490 - accuracy: 0.4726 - loss: 1.06510
Epoch 32/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.5937 - Precision: 0.4322 - Recall: 0.2250 - accuracy: 0.4684 - loss: 1.0870
Epoch 33/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6082 - Precision: 0.4695 - Recall: 0.3190 - accuracy: 0.5000 - loss: 1.0586
Epoch 34/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6122 - Precision: 0.4220 - Recall: 0.2179 - accuracy: 0.4940 - loss: 1.0497   
Epoch 35/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6261 - Precision: 0.4592 - Recall: 0.2765 - accuracy: 0.5203 - loss: 1.0460  
Epoch 36/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.6088 - Precision: 0.3366 - Recall: 0.1510 - accuracy: 0.4782 - loss: 1.0590
Epoch 37/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6302 - Precision: 0.4277 - Recall: 0.2706 - accuracy: 0.4904 - loss: 1.0463
Epoch 38/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6086 - Precision: 0.3168 - Recall: 0.1413 - accuracy: 0.4852 - loss: 1.0539
Epoch 39/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6166 - Precision: 0.4812 - Recall: 0.1404 - accuracy: 0.4955 - loss: 1.0558
Epoch 40/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5970 - Precision: 0.2299 - Recall: 0.0703 - accuracy: 0.4655 - loss: 1.0701      
Epoch 41/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6204 - Precision: 0.5110 - Recall: 0.2490 - accuracy: 0.4844 - loss: 1.0545
Epoch 42/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6232 - Precision: 0.4816 - Recall: 0.2622 - accuracy: 0.4874 - loss: 1.0567
Epoch 43/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5611 - Precision: 0.4088 - Recall: 0.1888 - accuracy: 0.4437 - loss: 1.0941
Epoch 44/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6052 - Precision: 0.4650 - Recall: 0.3064 - accuracy: 0.4755 - loss: 1.0669
Epoch 45/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6174 - Precision: 0.3600 - Recall: 0.0777 - accuracy: 0.5107 - loss: 1.0435
Epoch 46/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6474 - Precision: 0.4750 - Recall: 0.3301 - accuracy: 0.5414 - loss: 1.0189
Epoch 47/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5861 - Precision: 0.3258 - Recall: 0.0948 - accuracy: 0.4986 - loss: 1.0678
Epoch 48/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.6038 - Precision: 0.4470 - Recall: 0.2666 - accuracy: 0.5057 - loss: 1.0451
Epoch 49/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5892 - Precision: 0.2689 - Recall: 0.0980 - accuracy: 0.4748 - loss: 1.0609     
Epoch 50/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6327 - Precision: 0.2702 - Recall: 0.0908 - accuracy: 0.5118 - loss: 1.0402
5/5 ━━━━━━━━━━━━━━━━━━━━ 1s 71ms/step
Epoch 1/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 6s 7ms/step - AUC: 0.5565 - Precision: 0.4136 - Recall: 0.2635 - accuracy: 0.4113 - loss: 8.8693
Epoch 2/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6260 - Precision: 0.5236 - Recall: 0.2009 - accuracy: 0.4934 - loss: 3.0863
Epoch 3/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6144 - Precision: 0.4270 - Recall: 0.1920 - accuracy: 0.5107 - loss: 1.5445
Epoch 4/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 9ms/step - AUC: 0.6288 - Precision: 0.5268 - Recall: 0.3799 - accuracy: 0.4927 - loss: 2.1038
Epoch 5/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 9ms/step - AUC: 0.6176 - Precision: 0.4734 - Recall: 0.2140 - accuracy: 0.4899 - loss: 3.1784
Epoch 6/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6054 - Precision: 0.4551 - Recall: 0.1929 - accuracy: 0.4711 - loss: 1.2548
Epoch 7/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6054 - Precision: 0.4409 - Recall: 0.1700 - accuracy: 0.4282 - loss: 1.0588
Epoch 8/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.5958 - Precision: 0.4188 - Recall: 0.1555 - accuracy: 0.4684 - loss: 1.0749
Epoch 9/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.5684 - Precision: 0.3538 - Recall: 0.1285 - accuracy: 0.4264 - loss: 1.0926
Epoch 10/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.5889 - Precision: 0.4898 - Recall: 0.2761 - accuracy: 0.4525 - loss: 1.0798
Epoch 11/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6141 - Precision: 0.4316 - Recall: 0.1841 - accuracy: 0.4394 - loss: 1.0666
Epoch 12/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.5907 - Precision: 0.4598 - Recall: 0.2715 - accuracy: 0.4763 - loss: 1.0778
Epoch 13/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5841 - Precision: 0.4571 - Recall: 0.2376 - accuracy: 0.4646 - loss: 1.9033
Epoch 14/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6015 - Precision: 0.4809 - Recall: 0.3098 - accuracy: 0.5021 - loss: 1.0977
Epoch 15/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6270 - Precision: 0.3165 - Recall: 0.0919 - accuracy: 0.4842 - loss: 1.0490
Epoch 16/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5878 - Precision: 0.3989 - Recall: 0.1611 - accuracy: 0.4360 - loss: 1.0717
Epoch 17/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5731 - Precision: 0.4203 - Recall: 0.1790 - accuracy: 0.4542 - loss: 1.0902
Epoch 18/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5902 - Precision: 0.4673 - Recall: 0.3570 - accuracy: 0.4800 - loss: 1.0774
Epoch 19/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6069 - Precision: 0.4209 - Recall: 0.0588 - accuracy: 0.4843 - loss: 1.0612
Epoch 20/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5991 - Precision: 0.4614 - Recall: 0.3038 - accuracy: 0.4933 - loss: 1.0703
Epoch 21/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6010 - Precision: 0.3490 - Recall: 0.0887 - accuracy: 0.5014 - loss: 1.0580
Epoch 22/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6078 - Precision: 0.4486 - Recall: 0.1869 - accuracy: 0.4993 - loss: 1.0673
Epoch 23/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5938 - Precision: 0.4550 - Recall: 0.2406 - accuracy: 0.4860 - loss: 1.0673
Epoch 24/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6002 - Precision: 0.4307 - Recall: 0.2479 - accuracy: 0.4933 - loss: 1.0667
Epoch 25/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5886 - Precision: 0.3573 - Recall: 0.0948 - accuracy: 0.4676 - loss: 1.0788
Epoch 26/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6171 - Precision: 0.4883 - Recall: 0.3252 - accuracy: 0.4993 - loss: 1.0618
Epoch 27/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6222 - Precision: 0.4578 - Recall: 0.2759 - accuracy: 0.4868 - loss: 1.0530
Epoch 28/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6248 - Precision: 0.5069 - Recall: 0.3340 - accuracy: 0.4472 - loss: 1.0583
Epoch 29/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.5983 - Precision: 0.4349 - Recall: 0.1620 - accuracy: 0.4787 - loss: 3.8202
Epoch 30/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6263 - Precision: 0.5190 - Recall: 0.3858 - accuracy: 0.5020 - loss: 1.0584
Epoch 31/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6051 - Precision: 0.4783 - Recall: 0.3342 - accuracy: 0.5245 - loss: 1.0548
Epoch 32/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6243 - Precision: 0.4323 - Recall: 0.1704 - accuracy: 0.5141 - loss: 1.0556
Epoch 33/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6216 - Precision: 0.4893 - Recall: 0.2397 - accuracy: 0.4993 - loss: 1.4362
Epoch 34/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5954 - Precision: 0.4949 - Recall: 0.1109 - accuracy: 0.4709 - loss: 1.0675
Epoch 35/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6287 - Precision: 0.4891 - Recall: 0.2625 - accuracy: 0.5109 - loss: 1.0389
Epoch 36/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6089 - Precision: 0.4724 - Recall: 0.2737 - accuracy: 0.5054 - loss: 1.0584
Epoch 37/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6244 - Precision: 0.4202 - Recall: 0.1925 - accuracy: 0.5010 - loss: 1.0546
Epoch 38/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6011 - Precision: 0.4889 - Recall: 0.3360 - accuracy: 0.5022 - loss: 1.0602
Epoch 39/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5856 - Precision: 0.4056 - Recall: 0.1979 - accuracy: 0.4502 - loss: 1.0706
Epoch 40/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6375 - Precision: 0.4810 - Recall: 0.2835 - accuracy: 0.5287 - loss: 1.0330
Epoch 41/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5934 - Precision: 0.3680 - Recall: 0.1338 - accuracy: 0.4687 - loss: 1.0740
Epoch 42/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6269 - Precision: 0.4470 - Recall: 0.1583 - accuracy: 0.4960 - loss: 1.0548
Epoch 43/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6302 - Precision: 0.4963 - Recall: 0.2919 - accuracy: 0.5089 - loss: 1.0597
Epoch 44/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5966 - Precision: 0.4042 - Recall: 0.1481 - accuracy: 0.4913 - loss: 1.0628
Epoch 45/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6112 - Precision: 0.4917 - Recall: 0.3007 - accuracy: 0.5206 - loss: 1.0509
Epoch 46/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6472 - Precision: 0.4466 - Recall: 0.2163 - accuracy: 0.5102 - loss: 1.0391
Epoch 47/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6218 - Precision: 0.5044 - Recall: 0.3482 - accuracy: 0.5185 - loss: 1.0428
Epoch 48/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6252 - Precision: 0.4503 - Recall: 0.2585 - accuracy: 0.5052 - loss: 1.0550
Epoch 49/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6114 - Precision: 0.4903 - Recall: 0.2832 - accuracy: 0.4988 - loss: 1.0727
Epoch 50/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6024 - Precision: 0.4191 - Recall: 0.1875 - accuracy: 0.4785 - loss: 1.9084
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 33ms/step
Epoch 1/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 5s 7ms/step - AUC: 0.5497 - Precision: 0.4026 - Recall: 0.3224 - accuracy: 0.4085 - loss: 5.2218
Epoch 2/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5996 - Precision: 0.4180 - Recall: 0.0449 - accuracy: 0.4889 - loss: 1.2320
Epoch 3/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6369 - Precision: 0.5414 - Recall: 0.3385 - accuracy: 0.5237 - loss: 1.4395
Epoch 4/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6252 - Precision: 0.5195 - Recall: 0.3726 - accuracy: 0.5105 - loss: 1.5043
Epoch 5/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6322 - Precision: 0.4608 - Recall: 0.2669 - accuracy: 0.5152 - loss: 1.1478
Epoch 6/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5877 - Precision: 0.4193 - Recall: 0.1139 - accuracy: 0.4786 - loss: 1.0782
Epoch 7/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6323 - Precision: 0.5296 - Recall: 0.3574 - accuracy: 0.5123 - loss: 1.0303
Epoch 8/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6237 - Precision: 0.4928 - Recall: 0.3629 - accuracy: 0.5078 - loss: 1.4039
Epoch 9/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6026 - Precision: 0.3474 - Recall: 0.1305 - accuracy: 0.4674 - loss: 2.4843
Epoch 10/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6045 - Precision: 0.3723 - Recall: 0.1826 - accuracy: 0.4906 - loss: 1.0543
Epoch 11/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5705 - Precision: 0.3191 - Recall: 0.0867 - accuracy: 0.4733 - loss: 1.1848
Epoch 12/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6038 - Precision: 0.4650 - Recall: 0.2935 - accuracy: 0.5067 - loss: 1.0481
Epoch 13/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6010 - Precision: 0.3600 - Recall: 0.1217 - accuracy: 0.4745 - loss: 1.1116
Epoch 14/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6008 - Precision: 0.4633 - Recall: 0.2668 - accuracy: 0.4771 - loss: 1.0760
Epoch 15/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6399 - Precision: 0.4847 - Recall: 0.3058 - accuracy: 0.5361 - loss: 1.0324
Epoch 16/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6078 - Precision: 0.2316 - Recall: 0.0497 - accuracy: 0.4840 - loss: 1.0730 
Epoch 17/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6266 - Precision: 0.4794 - Recall: 0.3018 - accuracy: 0.5010 - loss: 1.0436
Epoch 18/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6282 - Precision: 0.3617 - Recall: 0.1594 - accuracy: 0.5187 - loss: 1.0417
Epoch 19/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6285 - Precision: 0.4070 - Recall: 0.1842 - accuracy: 0.5048 - loss: 1.0464
Epoch 20/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6330 - Precision: 0.4169 - Recall: 0.1747 - accuracy: 0.5071 - loss: 1.0437
Epoch 21/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6004 - Precision: 0.4888 - Recall: 0.3606 - accuracy: 0.4939 - loss: 1.0580
Epoch 22/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6085 - Precision: 0.3676 - Recall: 0.1452 - accuracy: 0.4659 - loss: 1.0645
Epoch 23/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5743 - Precision: 0.2179 - Recall: 0.0402 - accuracy: 0.4739 - loss: 1.0783
Epoch 24/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6327 - Precision: 0.5219 - Recall: 0.2588 - accuracy: 0.5105 - loss: 1.0348
Epoch 25/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6120 - Precision: 0.5008 - Recall: 0.3264 - accuracy: 0.5075 - loss: 6.3290
Epoch 26/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6125 - Precision: 0.2483 - Recall: 0.0708 - accuracy: 0.4744 - loss: 1.0589
Epoch 27/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.5971 - Precision: 0.2094 - Recall: 0.0487 - accuracy: 0.4820 - loss: 1.0727
Epoch 28/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6082 - Precision: 0.4847 - Recall: 0.1568 - accuracy: 0.4882 - loss: 1.0595
Epoch 29/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6291 - Precision: 0.5207 - Recall: 0.4486 - accuracy: 0.5246 - loss: 1.0336
Epoch 30/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5891 - Precision: 0.3385 - Recall: 0.1103 - accuracy: 0.4481 - loss: 1.0724
Epoch 31/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6075 - Precision: 0.3688 - Recall: 0.1857 - accuracy: 0.4951 - loss: 1.0525
Epoch 32/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6301 - Precision: 0.4940 - Recall: 0.3088 - accuracy: 0.4913 - loss: 1.0433
Epoch 33/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6241 - Precision: 0.5392 - Recall: 0.2011 - accuracy: 0.4988 - loss: 1.0442
Epoch 34/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6033 - Precision: 0.3778 - Recall: 0.1429 - accuracy: 0.5035 - loss: 1.0602
Epoch 35/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 3ms/step - AUC: 0.6165 - Precision: 0.4559 - Recall: 0.2364 - accuracy: 0.5108 - loss: 1.0538
Epoch 36/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6168 - Precision: 0.4549 - Recall: 0.2639 - accuracy: 0.4953 - loss: 1.0465
Epoch 37/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6410 - Precision: 0.5312 - Recall: 0.3293 - accuracy: 0.5199 - loss: 1.0318
Epoch 38/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6009 - Precision: 0.3534 - Recall: 0.0693 - accuracy: 0.4936 - loss: 1.0583
Epoch 39/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6170 - Precision: 0.4232 - Recall: 0.2201 - accuracy: 0.5106 - loss: 1.0408
Epoch 40/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6100 - Precision: 0.5056 - Recall: 0.2460 - accuracy: 0.4822 - loss: 1.0628
Epoch 41/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6133 - Precision: 0.5100 - Recall: 0.3605 - accuracy: 0.4849 - loss: 1.0496
Epoch 42/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6037 - Precision: 0.4150 - Recall: 0.2009 - accuracy: 0.4858 - loss: 1.0596
Epoch 43/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6058 - Precision: 0.3514 - Recall: 0.1595 - accuracy: 0.4849 - loss: 1.0581
Epoch 44/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6087 - Precision: 0.4050 - Recall: 0.1656 - accuracy: 0.5035 - loss: 1.1027
Epoch 45/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6147 - Precision: 0.4563 - Recall: 0.2281 - accuracy: 0.5122 - loss: 1.0373
Epoch 46/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6118 - Precision: 0.2791 - Recall: 0.0851 - accuracy: 0.4779 - loss: 1.0570
Epoch 47/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6033 - Precision: 0.3934 - Recall: 0.0726 - accuracy: 0.4772 - loss: 1.0610
Epoch 48/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6056 - Precision: 0.4899 - Recall: 0.3281 - accuracy: 0.4993 - loss: 1.0506
Epoch 49/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6132 - Precision: 0.4393 - Recall: 0.1714 - accuracy: 0.4954 - loss: 1.0502
Epoch 50/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6214 - Precision: 0.4858 - Recall: 0.2256 - accuracy: 0.4928 - loss: 1.0498
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 32ms/step
Epoch 1/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 4s 8ms/step - AUC: 0.5669 - Precision: 0.4075 - Recall: 0.2796 - accuracy: 0.4067 - loss: 2.3423
Epoch 2/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6002 - Precision: 0.5085 - Recall: 0.3760 - accuracy: 0.4944 - loss: 1.6038
Epoch 3/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5979 - Precision: 0.3418 - Recall: 0.0271 - accuracy: 0.4947 - loss: 1.1424
Epoch 4/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6002 - Precision: 0.4592 - Recall: 0.2744 - accuracy: 0.4759 - loss: 1.1693
Epoch 5/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6024 - Precision: 0.3436 - Recall: 0.0781 - accuracy: 0.4901 - loss: 1.3648
Epoch 6/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5873 - Precision: 0.2849 - Recall: 0.1193 - accuracy: 0.4584 - loss: 1.1061    
Epoch 7/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6165 - Precision: 0.4900 - Recall: 0.4202 - accuracy: 0.5010 - loss: 1.0566
Epoch 8/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6264 - Precision: 0.3042 - Recall: 0.0961 - accuracy: 0.5230 - loss: 1.0371  
Epoch 9/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6276 - Precision: 0.4216 - Recall: 0.2000 - accuracy: 0.5329 - loss: 1.0412  
Epoch 10/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6139 - Precision: 0.4191 - Recall: 0.2227 - accuracy: 0.5185 - loss: 1.0415 
Epoch 11/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6429 - Precision: 0.3181 - Recall: 0.1163 - accuracy: 0.5427 - loss: 1.0312
Epoch 12/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6351 - Precision: 0.3544 - Recall: 0.1711 - accuracy: 0.5149 - loss: 1.0384
Epoch 13/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5869 - Precision: 0.2829 - Recall: 0.0943 - accuracy: 0.4583 - loss: 1.1629  
Epoch 14/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6020 - Precision: 0.4060 - Recall: 0.1652 - accuracy: 0.4764 - loss: 1.0778
Epoch 15/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5859 - Precision: 0.4133 - Recall: 0.1333 - accuracy: 0.4658 - loss: 1.0739
Epoch 16/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6299 - Precision: 0.4804 - Recall: 0.3120 - accuracy: 0.4941 - loss: 2.0031
Epoch 17/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6293 - Precision: 0.4695 - Recall: 0.3826 - accuracy: 0.5122 - loss: 1.9764 
Epoch 18/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5664 - Precision: 0.2262 - Recall: 0.0695 - accuracy: 0.4620 - loss: 1.0731  
Epoch 19/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6113 - Precision: 0.4870 - Recall: 0.4251 - accuracy: 0.4854 - loss: 1.0567
Epoch 20/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6126 - Precision: 0.3692 - Recall: 0.0997 - accuracy: 0.4833 - loss: 2.0728 
Epoch 21/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6317 - Precision: 0.5264 - Recall: 0.4616 - accuracy: 0.5243 - loss: 1.0352
Epoch 22/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6443 - Precision: 0.2542 - Recall: 0.0484 - accuracy: 0.5255 - loss: 1.0322 
Epoch 23/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5902 - Precision: 0.1555 - Recall: 0.0296 - accuracy: 0.4587 - loss: 1.0674    
Epoch 24/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6197 - Precision: 0.5123 - Recall: 0.4418 - accuracy: 0.5076 - loss: 1.0424
Epoch 25/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6334 - Precision: 0.4413 - Recall: 0.2559 - accuracy: 0.5199 - loss: 1.0876
Epoch 26/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6284 - Precision: 0.5369 - Recall: 0.2596 - accuracy: 0.5064 - loss: 1.04270
Epoch 27/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6267 - Precision: 0.3319 - Recall: 0.1247 - accuracy: 0.5220 - loss: 1.0488
Epoch 28/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6019 - Precision: 0.2913 - Recall: 0.0691 - accuracy: 0.4751 - loss: 1.0573
Epoch 29/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5906 - Precision: 0.4337 - Recall: 0.2536 - accuracy: 0.4751 - loss: 1.0706
Epoch 30/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6157 - Precision: 0.3552 - Recall: 0.1864 - accuracy: 0.4896 - loss: 1.0495 
Epoch 31/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6073 - Precision: 0.1391 - Recall: 0.0242 - accuracy: 0.4976 - loss: 1.0520     
Epoch 32/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5826 - Precision: 0.4510 - Recall: 0.1639 - accuracy: 0.4728 - loss: 1.0708
Epoch 33/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.5950 - Precision: 0.4518 - Recall: 0.3166 - accuracy: 0.4748 - loss: 1.0704
Epoch 34/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6401 - Precision: 0.4695 - Recall: 0.2834 - accuracy: 0.5244 - loss: 1.0292 
Epoch 35/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5897 - Precision: 0.3972 - Recall: 0.2096 - accuracy: 0.4845 - loss: 1.0665
Epoch 36/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5807 - Precision: 0.3881 - Recall: 0.1930 - accuracy: 0.4538 - loss: 1.0803
Epoch 37/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5990 - Precision: 0.4449 - Recall: 0.2796 - accuracy: 0.4673 - loss: 1.0716
Epoch 38/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6172 - Precision: 0.4967 - Recall: 0.4078 - accuracy: 0.5063 - loss: 1.0414
Epoch 39/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6181 - Precision: 0.2855 - Recall: 0.1060 - accuracy: 0.5083 - loss: 1.0404   
Epoch 40/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5987 - Precision: 0.2771 - Recall: 0.0870 - accuracy: 0.4735 - loss: 1.0609    
Epoch 41/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5904 - Precision: 0.2938 - Recall: 0.0446 - accuracy: 0.4902 - loss: 1.0492   
Epoch 42/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5888 - Precision: 0.0440 - Recall: 0.0016 - accuracy: 0.4625 - loss: 1.2599       
Epoch 43/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6230 - Precision: 0.5198 - Recall: 0.4090 - accuracy: 0.5213 - loss: 1.0298
Epoch 44/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6177 - Precision: 0.3943 - Recall: 0.2087 - accuracy: 0.5220 - loss: 1.0377 
Epoch 45/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6012 - Precision: 0.3106 - Recall: 0.1076 - accuracy: 0.4737 - loss: 1.0606 
Epoch 46/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6297 - Precision: 0.3452 - Recall: 0.1240 - accuracy: 0.5194 - loss: 1.0378    
Epoch 47/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5902 - Precision: 0.2698 - Recall: 0.0798 - accuracy: 0.4732 - loss: 1.0667  
Epoch 48/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6183 - Precision: 0.4080 - Recall: 0.2150 - accuracy: 0.4900 - loss: 1.0470    
Epoch 49/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6193 - Precision: 0.2532 - Recall: 0.0793 - accuracy: 0.4923 - loss: 1.0504    
Epoch 50/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6221 - Precision: 0.3454 - Recall: 0.1440 - accuracy: 0.5312 - loss: 1.0279   
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 26ms/step
Epoch 1/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 5s 7ms/step - AUC: 0.5029 - Precision: 0.3618 - Recall: 0.3206 - accuracy: 0.3718 - loss: 52.7544
Epoch 2/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6165 - Precision: 0.5108 - Recall: 0.3498 - accuracy: 0.5013 - loss: 21.1288
Epoch 3/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6130 - Precision: 0.3168 - Recall: 0.1086 - accuracy: 0.4867 - loss: 3.8516
Epoch 4/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5979 - Precision: 0.4566 - Recall: 0.2127 - accuracy: 0.4525 - loss: 1.9302
Epoch 5/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6270 - Precision: 0.5126 - Recall: 0.3637 - accuracy: 0.5213 - loss: 1.3227
Epoch 6/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6097 - Precision: 0.4673 - Recall: 0.1915 - accuracy: 0.5025 - loss: 1.0490
Epoch 7/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6103 - Precision: 0.5057 - Recall: 0.2868 - accuracy: 0.5064 - loss: 1.0973
Epoch 8/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6191 - Precision: 0.5161 - Recall: 0.2524 - accuracy: 0.4765 - loss: 1.0548
Epoch 9/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6123 - Precision: 0.4892 - Recall: 0.3447 - accuracy: 0.4892 - loss: 1.0585
Epoch 10/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5949 - Precision: 0.4564 - Recall: 0.1864 - accuracy: 0.4732 - loss: 3.2908
Epoch 11/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5959 - Precision: 0.4605 - Recall: 0.2168 - accuracy: 0.4843 - loss: 1.1373
Epoch 12/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6266 - Precision: 0.4454 - Recall: 0.2370 - accuracy: 0.4879 - loss: 1.0524
Epoch 13/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6003 - Precision: 0.4313 - Recall: 0.2289 - accuracy: 0.4792 - loss: 1.0656
Epoch 14/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5780 - Precision: 0.3900 - Recall: 0.1997 - accuracy: 0.4725 - loss: 1.0890
Epoch 15/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6229 - Precision: 0.4669 - Recall: 0.2588 - accuracy: 0.5103 - loss: 2.2652
Epoch 16/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5763 - Precision: 0.3887 - Recall: 0.1238 - accuracy: 0.4780 - loss: 1.0739
Epoch 17/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5856 - Precision: 0.3768 - Recall: 0.1340 - accuracy: 0.4792 - loss: 1.0717
Epoch 18/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.6317 - Precision: 0.5265 - Recall: 0.3853 - accuracy: 0.5274 - loss: 1.0278
Epoch 19/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 4ms/step - AUC: 0.5777 - Precision: 0.4175 - Recall: 0.1603 - accuracy: 0.4664 - loss: 1.2794
Epoch 20/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6337 - Precision: 0.5175 - Recall: 0.3747 - accuracy: 0.5266 - loss: 1.0285
Epoch 21/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.5389 - Precision: 0.3239 - Recall: 0.1127 - accuracy: 0.3748 - loss: 1.1003
Epoch 22/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6126 - Precision: 0.4505 - Recall: 0.2438 - accuracy: 0.5055 - loss: 1.0530
Epoch 23/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6099 - Precision: 0.4500 - Recall: 0.2065 - accuracy: 0.5075 - loss: 1.0509
Epoch 24/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6047 - Precision: 0.3666 - Recall: 0.1186 - accuracy: 0.5032 - loss: 1.0458
Epoch 25/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6080 - Precision: 0.3625 - Recall: 0.1003 - accuracy: 0.4697 - loss: 1.0674
Epoch 26/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6029 - Precision: 0.4734 - Recall: 0.2726 - accuracy: 0.5035 - loss: 1.0670
Epoch 27/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6149 - Precision: 0.4796 - Recall: 0.3349 - accuracy: 0.5075 - loss: 1.0464
Epoch 28/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6332 - Precision: 0.4856 - Recall: 0.2815 - accuracy: 0.5158 - loss: 1.0404
Epoch 29/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6410 - Precision: 0.4820 - Recall: 0.2074 - accuracy: 0.5071 - loss: 1.0434
Epoch 30/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6177 - Precision: 0.4639 - Recall: 0.2311 - accuracy: 0.5031 - loss: 1.0597
Epoch 31/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6125 - Precision: 0.4019 - Recall: 0.1632 - accuracy: 0.4780 - loss: 1.0605
Epoch 32/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6325 - Precision: 0.4150 - Recall: 0.1370 - accuracy: 0.4998 - loss: 1.0489
Epoch 33/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6411 - Precision: 0.5201 - Recall: 0.2365 - accuracy: 0.5122 - loss: 1.0375
Epoch 34/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5933 - Precision: 0.4571 - Recall: 0.2198 - accuracy: 0.4683 - loss: 1.0710
Epoch 35/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5957 - Precision: 0.2836 - Recall: 0.0868 - accuracy: 0.4576 - loss: 1.0733
Epoch 36/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6027 - Precision: 0.4728 - Recall: 0.2704 - accuracy: 0.4850 - loss: 1.0782
Epoch 37/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6023 - Precision: 0.4800 - Recall: 0.3859 - accuracy: 0.4922 - loss: 1.0615
Epoch 38/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6104 - Precision: 0.5056 - Recall: 0.2950 - accuracy: 0.5001 - loss: 1.0591
Epoch 39/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5647 - Precision: 0.3237 - Recall: 0.1304 - accuracy: 0.4228 - loss: 1.0892
Epoch 40/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6131 - Precision: 0.4171 - Recall: 0.1373 - accuracy: 0.4973 - loss: 1.0605
Epoch 41/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6275 - Precision: 0.4608 - Recall: 0.2102 - accuracy: 0.4997 - loss: 1.0508
Epoch 42/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6101 - Precision: 0.4167 - Recall: 0.1988 - accuracy: 0.4753 - loss: 1.0641
Epoch 43/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6066 - Precision: 0.3434 - Recall: 0.1050 - accuracy: 0.4843 - loss: 1.0622
Epoch 44/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6222 - Precision: 0.5233 - Recall: 0.3517 - accuracy: 0.5155 - loss: 1.0491
Epoch 45/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6033 - Precision: 0.4190 - Recall: 0.2259 - accuracy: 0.5096 - loss: 1.0717
Epoch 46/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5921 - Precision: 0.4446 - Recall: 0.1830 - accuracy: 0.4784 - loss: 1.0722
Epoch 47/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6364 - Precision: 0.5250 - Recall: 0.3634 - accuracy: 0.5399 - loss: 1.0260
Epoch 48/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5943 - Precision: 0.3629 - Recall: 0.1522 - accuracy: 0.4902 - loss: 1.0655
Epoch 49/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6039 - Precision: 0.3792 - Recall: 0.1544 - accuracy: 0.4817 - loss: 1.0599
Epoch 50/50
146/146 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6279 - Precision: 0.4871 - Recall: 0.2693 - accuracy: 0.5215 - loss: 1.0457
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 36ms/step
Epoch 1/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 6s 9ms/step - AUC: 0.5209 - Precision: 0.3670 - Recall: 0.3034 - accuracy: 0.3735 - loss: 14.7581
Epoch 2/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6170 - Precision: 0.4204 - Recall: 0.1277 - accuracy: 0.4946 - loss: 10.0535
Epoch 3/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6075 - Precision: 0.4413 - Recall: 0.1302 - accuracy: 0.4782 - loss: 1.6304
Epoch 4/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 9ms/step - AUC: 0.6065 - Precision: 0.4600 - Recall: 0.1402 - accuracy: 0.4796 - loss: 1.5227
Epoch 5/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 9ms/step - AUC: 0.5765 - Precision: 0.4256 - Recall: 0.2525 - accuracy: 0.4691 - loss: 1.0879
Epoch 6/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6248 - Precision: 0.3983 - Recall: 0.1470 - accuracy: 0.4973 - loss: 1.0486
Epoch 7/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5887 - Precision: 0.2729 - Recall: 0.1053 - accuracy: 0.4843 - loss: 1.2315
Epoch 8/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.5814 - Precision: 0.2848 - Recall: 0.0789 - accuracy: 0.4283 - loss: 1.0765
Epoch 9/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6073 - Precision: 0.5007 - Recall: 0.3154 - accuracy: 0.4920 - loss: 1.2648
Epoch 10/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6106 - Precision: 0.3942 - Recall: 0.0921 - accuracy: 0.4892 - loss: 1.0535
Epoch 11/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6197 - Precision: 0.4801 - Recall: 0.3172 - accuracy: 0.4928 - loss: 1.0597
Epoch 12/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6026 - Precision: 0.3265 - Recall: 0.0534 - accuracy: 0.4861 - loss: 1.0597
Epoch 13/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 9ms/step - AUC: 0.6200 - Precision: 0.5021 - Recall: 0.2251 - accuracy: 0.4894 - loss: 1.0570
Epoch 14/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6026 - Precision: 0.4411 - Recall: 0.1344 - accuracy: 0.4864 - loss: 1.0568
Epoch 15/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6104 - Precision: 0.4852 - Recall: 0.2774 - accuracy: 0.4937 - loss: 1.0618
Epoch 16/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.5957 - Precision: 0.4618 - Recall: 0.1980 - accuracy: 0.4922 - loss: 1.0586
Epoch 17/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6249 - Precision: 0.5149 - Recall: 0.3511 - accuracy: 0.5101 - loss: 1.0417
Epoch 18/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5929 - Precision: 0.3462 - Recall: 0.1368 - accuracy: 0.4768 - loss: 1.0664
Epoch 19/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6150 - Precision: 0.5046 - Recall: 0.3016 - accuracy: 0.4929 - loss: 1.0552
Epoch 20/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6450 - Precision: 0.4165 - Recall: 0.2004 - accuracy: 0.5243 - loss: 1.0383
Epoch 21/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5686 - Precision: 0.3498 - Recall: 0.1074 - accuracy: 0.4904 - loss: 1.0622
Epoch 22/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 8ms/step - AUC: 0.6176 - Precision: 0.5007 - Recall: 0.3288 - accuracy: 0.4965 - loss: 1.0498
Epoch 23/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5776 - Precision: 0.2727 - Recall: 0.0572 - accuracy: 0.4130 - loss: 1.0812
Epoch 24/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6171 - Precision: 0.4715 - Recall: 0.2577 - accuracy: 0.5006 - loss: 1.0600
Epoch 25/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6095 - Precision: 0.4312 - Recall: 0.2323 - accuracy: 0.4894 - loss: 1.0572
Epoch 26/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.5829 - Precision: 0.4380 - Recall: 0.2723 - accuracy: 0.4865 - loss: 1.0621
Epoch 27/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6068 - Precision: 0.3124 - Recall: 0.0922 - accuracy: 0.4729 - loss: 1.0640
Epoch 28/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6070 - Precision: 0.4979 - Recall: 0.3212 - accuracy: 0.4964 - loss: 1.0507
Epoch 29/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6642 - Precision: 0.5171 - Recall: 0.3345 - accuracy: 0.5238 - loss: 1.0191
Epoch 30/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6193 - Precision: 0.3249 - Recall: 0.1011 - accuracy: 0.4846 - loss: 1.0600
Epoch 31/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6223 - Precision: 0.5287 - Recall: 0.4649 - accuracy: 0.5132 - loss: 1.0312
Epoch 32/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6276 - Precision: 0.5354 - Recall: 0.5043 - accuracy: 0.5298 - loss: 1.0321
Epoch 33/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6065 - Precision: 0.4083 - Recall: 0.1560 - accuracy: 0.4912 - loss: 1.0607
Epoch 34/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6210 - Precision: 0.4364 - Recall: 0.2144 - accuracy: 0.5072 - loss: 1.0554
Epoch 35/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 9ms/step - AUC: 0.6099 - Precision: 0.3593 - Recall: 0.1301 - accuracy: 0.4904 - loss: 1.0634
Epoch 36/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 14ms/step - AUC: 0.6198 - Precision: 0.3839 - Recall: 0.1780 - accuracy: 0.5063 - loss: 1.0415
Epoch 37/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.6126 - Precision: 0.4415 - Recall: 0.2479 - accuracy: 0.5204 - loss: 1.0450
Epoch 38/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 6ms/step - AUC: 0.5898 - Precision: 0.4475 - Recall: 0.1543 - accuracy: 0.4691 - loss: 1.0765
Epoch 39/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5962 - Precision: 0.4228 - Recall: 0.1652 - accuracy: 0.4693 - loss: 1.0728
Epoch 40/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.5943 - Precision: 0.4497 - Recall: 0.2788 - accuracy: 0.4852 - loss: 1.0762
Epoch 41/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6121 - Precision: 0.4913 - Recall: 0.3962 - accuracy: 0.4980 - loss: 1.0467
Epoch 42/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6220 - Precision: 0.4986 - Recall: 0.3641 - accuracy: 0.5002 - loss: 1.0444
Epoch 43/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6292 - Precision: 0.4121 - Recall: 0.1897 - accuracy: 0.5115 - loss: 1.0483
Epoch 44/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 5ms/step - AUC: 0.6264 - Precision: 0.4209 - Recall: 0.1859 - accuracy: 0.4937 - loss: 1.0515
Epoch 45/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6141 - Precision: 0.2687 - Recall: 0.0466 - accuracy: 0.5023 - loss: 1.0505
Epoch 46/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6261 - Precision: 0.4652 - Recall: 0.2485 - accuracy: 0.5332 - loss: 1.0319
Epoch 47/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 1s 7ms/step - AUC: 0.6290 - Precision: 0.4252 - Recall: 0.1787 - accuracy: 0.5248 - loss: 1.0503
Epoch 48/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6233 - Precision: 0.3699 - Recall: 0.1286 - accuracy: 0.5025 - loss: 1.0441
Epoch 49/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6114 - Precision: 0.3457 - Recall: 0.0841 - accuracy: 0.4857 - loss: 1.0554
Epoch 50/50
73/73 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.5825 - Precision: 0.3684 - Recall: 0.1263 - accuracy: 0.4808 - loss: 1.0703
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 28ms/step
Epoch 1/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 5s 10ms/step - AUC: 0.5413 - Precision: 0.3544 - Recall: 0.2835 - accuracy: 0.3578 - loss: 9.7574
Epoch 2/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6099 - Precision: 0.4815 - Recall: 0.4492 - accuracy: 0.4991 - loss: 7.8835
Epoch 3/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6016 - Precision: 0.3987 - Recall: 0.0381 - accuracy: 0.4885 - loss: 2.7958 
Epoch 4/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6194 - Precision: 0.4462 - Recall: 0.1609 - accuracy: 0.4782 - loss: 1.4607
Epoch 5/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6248 - Precision: 0.5969 - Recall: 0.0745 - accuracy: 0.5208 - loss: 1.0485
Epoch 6/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6532 - Precision: 0.4508 - Recall: 0.2392 - accuracy: 0.5446 - loss: 1.2881 
Epoch 7/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5902 - Precision: 0.1961 - Recall: 0.0559 - accuracy: 0.4643 - loss: 2.4603     
Epoch 8/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - AUC: 0.6250 - Precision: 0.5156 - Recall: 0.4353 - accuracy: 0.5114 - loss: 1.0546
Epoch 9/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5988 - Precision: 0.9086 - Recall: 0.0196 - accuracy: 0.4897 - loss: 1.0465
Epoch 10/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6095 - Precision: 0.4895 - Recall: 0.3066 - accuracy: 0.4905 - loss: 1.0523
Epoch 11/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6269 - Precision: 0.5079 - Recall: 0.5008 - accuracy: 0.5059 - loss: 1.7394
Epoch 12/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6229 - Precision: 0.4293 - Recall: 0.1048 - accuracy: 0.5098 - loss: 1.2826 
Epoch 13/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6180 - Precision: 0.3375 - Recall: 0.1469 - accuracy: 0.4948 - loss: 1.4560  
Epoch 14/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6156 - Precision: 0.3640 - Recall: 0.1920 - accuracy: 0.4989 - loss: 1.0469 
Epoch 15/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6120 - Precision: 0.3678 - Recall: 0.1630 - accuracy: 0.4916 - loss: 1.0575   
Epoch 16/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6299 - Precision: 0.4736 - Recall: 0.2804 - accuracy: 0.5261 - loss: 1.0356
Epoch 17/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6625 - Precision: 0.4390 - Recall: 0.2664 - accuracy: 0.5408 - loss: 1.0173
Epoch 18/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5681 - Precision: 0.2918 - Recall: 0.1024 - accuracy: 0.4161 - loss: 1.0891 
Epoch 19/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.5772 - Precision: 0.1928 - Recall: 0.0611 - accuracy: 0.4547 - loss: 1.0748  
Epoch 20/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6213 - Precision: 0.4826 - Recall: 0.3029 - accuracy: 0.4851 - loss: 1.0546
Epoch 21/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6112 - Precision: 0.4884 - Recall: 0.3119 - accuracy: 0.4872 - loss: 1.0573
Epoch 22/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6122 - Precision: 0.5179 - Recall: 0.4929 - accuracy: 0.5170 - loss: 1.0379
Epoch 23/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6360 - Precision: 0.2666 - Recall: 0.0910 - accuracy: 0.4957 - loss: 1.0494   
Epoch 24/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6145 - Precision: 0.3726 - Recall: 0.0736 - accuracy: 0.4887 - loss: 1.0858
Epoch 25/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5828 - Precision: 0.4556 - Recall: 0.3332 - accuracy: 0.4901 - loss: 1.0752
Epoch 26/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.6073 - Precision: 0.2440 - Recall: 0.0699 - accuracy: 0.4772 - loss: 1.0548
Epoch 27/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5856 - Precision: 0.4117 - Recall: 0.1572 - accuracy: 0.4682 - loss: 1.0698
Epoch 28/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.6067 - Precision: 0.4802 - Recall: 0.3011 - accuracy: 0.4851 - loss: 1.1464
Epoch 29/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6361 - Precision: 0.5142 - Recall: 0.4249 - accuracy: 0.5149 - loss: 1.0310
Epoch 30/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5960 - Precision: 0.3700 - Recall: 0.1494 - accuracy: 0.4905 - loss: 1.0551 
Epoch 31/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6016 - Precision: 0.4524 - Recall: 0.2198 - accuracy: 0.4888 - loss: 1.0517
Epoch 32/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5923 - Precision: 0.4488 - Recall: 0.2326 - accuracy: 0.4741 - loss: 1.0696
Epoch 33/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6175 - Precision: 0.5045 - Recall: 0.4374 - accuracy: 0.4997 - loss: 1.0528
Epoch 34/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.5923 - Precision: 0.4868 - Recall: 0.3289 - accuracy: 0.4852 - loss: 1.0620 
Epoch 35/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5895 - Precision: 0.4721 - Recall: 0.3585 - accuracy: 0.4732 - loss: 1.0757
Epoch 36/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.5837 - Precision: 0.4435 - Recall: 0.2931 - accuracy: 0.4796 - loss: 1.0686
Epoch 37/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.5798 - Precision: 0.4057 - Recall: 0.2008 - accuracy: 0.4880 - loss: 1.0574
Epoch 38/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5760 - Precision: 0.3245 - Recall: 0.1036 - accuracy: 0.4770 - loss: 1.0629
Epoch 39/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5723 - Precision: 0.4184 - Recall: 0.2136 - accuracy: 0.4659 - loss: 1.0706
Epoch 40/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6305 - Precision: 0.4772 - Recall: 0.3819 - accuracy: 0.4970 - loss: 1.0535
Epoch 41/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6117 - Precision: 0.1145 - Recall: 0.0137 - accuracy: 0.4868 - loss: 1.0550        
Epoch 42/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6379 - Precision: 0.5075 - Recall: 0.3595 - accuracy: 0.5084 - loss: 1.0370
Epoch 43/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.6319 - Precision: 0.4962 - Recall: 0.4152 - accuracy: 0.5192 - loss: 1.0293
Epoch 44/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6123 - Precision: 0.1807 - Recall: 0.0392 - accuracy: 0.4962 - loss: 1.0547  
Epoch 45/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6410 - Precision: 0.5186 - Recall: 0.2680 - accuracy: 0.5232 - loss: 1.0243
Epoch 46/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.5846 - Precision: 0.3252 - Recall: 0.1117 - accuracy: 0.4750 - loss: 1.0624 
Epoch 47/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.6296 - Precision: 0.5420 - Recall: 0.4441 - accuracy: 0.5293 - loss: 1.0267
Epoch 48/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.6467 - Precision: 0.4551 - Recall: 0.2686 - accuracy: 0.5248 - loss: 1.0330
Epoch 49/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.6273 - Precision: 0.3508 - Recall: 0.1345 - accuracy: 0.5080 - loss: 1.0449 
Epoch 50/50
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.5964 - Precision: 0.1862 - Recall: 0.0445 - accuracy: 0.4857 - loss: 1.0588     
5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 45ms/step
Best hyperparameter combination:
{'learning_rate': 0.001, 'dropout_rate': 0.4, 'batch_size': 16, 'accuracy': 0.7945205479452054, 'precision': 0.76454307568438, 'recall': 0.7729955229955231, 'f1': 0.7661143330571666}

Escogemos los mejores parámetros y entrenamos modelo

from keras.models import Sequential
from keras.layers import Dense, Dropout, BatchNormalization, Input
from keras.optimizers import Adam
from keras.callbacks import EarlyStopping

# Parámetros óptimos encontrados previamente
dropout_rate = 0.4
learning_rate = 0.001
batch_size = 16

input_dim = X_train_scaled.shape[1]
n_classes = Y_train_onehot.shape[1]

# Definición del modelo
best_model = Sequential([
    Input(shape=(input_dim,)),
    Dense(256, activation='relu'),
    BatchNormalization(),
    Dropout(dropout_rate),

    Dense(128, activation='tanh'),
    Dropout(dropout_rate),

    Dense(64, activation='relu'),
    Dropout(dropout_rate),

    Dense(32, activation='relu'),
    Dropout(dropout_rate),

    Dense(16, activation='relu'),
    Dense(n_classes, activation='softmax')
])

# Compilación del modelo
best_model.compile(
    optimizer=Adam(learning_rate=learning_rate),
    loss='categorical_crossentropy',
    metrics=['accuracy', 'Precision', 'Recall']
)

# EarlyStopping para prevenir sobreajuste
early_stop = EarlyStopping(
    monitor='val_loss',
    patience=10,
    restore_best_weights=True
)

# Entrenamiento con conjunto de validación
history = best_model.fit(
    X_train_scaled,
    Y_train_onehot,
    validation_data=(X_test_scaled, Y_test_onehot),
    epochs=100,
    batch_size=batch_size,
    callbacks=[early_stop],
    verbose=1
)

Epoch 1/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 9s 36ms/step - Precision: 0.3090 - Recall: 0.1513 - accuracy: 0.3255 - loss: 1.2461 - val_Precision: 1.0000 - val_Recall: 0.1301 - val_accuracy: 0.5000 - val_loss: 0.9917
Epoch 2/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - Precision: 0.6243 - Recall: 0.3434 - accuracy: 0.5097 - loss: 0.9603 - val_Precision: 0.9189 - val_Recall: 0.2329 - val_accuracy: 0.6164 - val_loss: 0.8791
Epoch 3/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7623 - Recall: 0.4047 - accuracy: 0.6008 - loss: 0.8322 - val_Precision: 0.9333 - val_Recall: 0.2877 - val_accuracy: 0.6644 - val_loss: 0.8002
Epoch 4/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7303 - Recall: 0.4607 - accuracy: 0.6031 - loss: 0.7765 - val_Precision: 0.9362 - val_Recall: 0.3014 - val_accuracy: 0.6781 - val_loss: 0.7590
Epoch 5/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7834 - Recall: 0.4947 - accuracy: 0.6447 - loss: 0.7335 - val_Precision: 0.9333 - val_Recall: 0.3836 - val_accuracy: 0.6575 - val_loss: 0.7193
Epoch 6/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7288 - Recall: 0.5164 - accuracy: 0.6357 - loss: 0.7262 - val_Precision: 0.9242 - val_Recall: 0.4178 - val_accuracy: 0.6986 - val_loss: 0.6731
Epoch 7/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - Precision: 0.7559 - Recall: 0.5393 - accuracy: 0.6625 - loss: 0.6738 - val_Precision: 0.9048 - val_Recall: 0.5205 - val_accuracy: 0.7123 - val_loss: 0.6501
Epoch 8/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - Precision: 0.7255 - Recall: 0.5454 - accuracy: 0.6645 - loss: 0.6646 - val_Precision: 0.8876 - val_Recall: 0.5411 - val_accuracy: 0.7192 - val_loss: 0.6450
Epoch 9/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - Precision: 0.7548 - Recall: 0.5778 - accuracy: 0.6727 - loss: 0.6325 - val_Precision: 0.8778 - val_Recall: 0.5411 - val_accuracy: 0.7329 - val_loss: 0.6283
Epoch 10/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7450 - Recall: 0.5880 - accuracy: 0.6669 - loss: 0.6419 - val_Precision: 0.8750 - val_Recall: 0.5753 - val_accuracy: 0.6986 - val_loss: 0.6129
Epoch 11/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7963 - Recall: 0.5836 - accuracy: 0.7035 - loss: 0.5603 - val_Precision: 0.8252 - val_Recall: 0.5822 - val_accuracy: 0.7123 - val_loss: 0.6418
Epoch 12/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7687 - Recall: 0.5799 - accuracy: 0.6818 - loss: 0.6573 - val_Precision: 0.8100 - val_Recall: 0.5548 - val_accuracy: 0.7055 - val_loss: 0.5969
Epoch 13/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - Precision: 0.7607 - Recall: 0.5620 - accuracy: 0.6456 - loss: 0.6385 - val_Precision: 0.8526 - val_Recall: 0.5548 - val_accuracy: 0.7055 - val_loss: 0.5928
Epoch 14/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7671 - Recall: 0.5730 - accuracy: 0.6767 - loss: 0.6090 - val_Precision: 0.8556 - val_Recall: 0.5274 - val_accuracy: 0.6712 - val_loss: 0.5984
Epoch 15/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7944 - Recall: 0.5817 - accuracy: 0.7148 - loss: 0.5871 - val_Precision: 0.8396 - val_Recall: 0.6096 - val_accuracy: 0.6918 - val_loss: 0.5937
Epoch 16/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7809 - Recall: 0.5916 - accuracy: 0.7254 - loss: 0.5335 - val_Precision: 0.8333 - val_Recall: 0.5822 - val_accuracy: 0.7192 - val_loss: 0.5980
Epoch 17/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - Precision: 0.7549 - Recall: 0.5900 - accuracy: 0.6868 - loss: 0.5441 - val_Precision: 0.8515 - val_Recall: 0.5890 - val_accuracy: 0.7123 - val_loss: 0.6013
Epoch 18/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7668 - Recall: 0.6205 - accuracy: 0.6994 - loss: 0.5715 - val_Precision: 0.8286 - val_Recall: 0.5959 - val_accuracy: 0.7329 - val_loss: 0.5744
Epoch 19/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7712 - Recall: 0.6227 - accuracy: 0.7151 - loss: 0.5802 - val_Precision: 0.8469 - val_Recall: 0.5685 - val_accuracy: 0.7466 - val_loss: 0.5545
Epoch 20/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - Precision: 0.7903 - Recall: 0.6332 - accuracy: 0.7384 - loss: 0.5223 - val_Precision: 0.8103 - val_Recall: 0.6438 - val_accuracy: 0.7192 - val_loss: 0.5614
Epoch 21/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7695 - Recall: 0.6430 - accuracy: 0.7247 - loss: 0.5445 - val_Precision: 0.8158 - val_Recall: 0.6370 - val_accuracy: 0.7192 - val_loss: 0.5765
Epoch 22/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.8077 - Recall: 0.6579 - accuracy: 0.7455 - loss: 0.5471 - val_Precision: 0.8376 - val_Recall: 0.6712 - val_accuracy: 0.7466 - val_loss: 0.5733
Epoch 23/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7798 - Recall: 0.5976 - accuracy: 0.7417 - loss: 0.5521 - val_Precision: 0.8205 - val_Recall: 0.6575 - val_accuracy: 0.7603 - val_loss: 0.5444
Epoch 24/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7700 - Recall: 0.6365 - accuracy: 0.7360 - loss: 0.5463 - val_Precision: 0.8130 - val_Recall: 0.6849 - val_accuracy: 0.7603 - val_loss: 0.5416
Epoch 25/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7648 - Recall: 0.6518 - accuracy: 0.7348 - loss: 0.5170 - val_Precision: 0.8099 - val_Recall: 0.6712 - val_accuracy: 0.7260 - val_loss: 0.5479
Epoch 26/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - Precision: 0.8154 - Recall: 0.6836 - accuracy: 0.7654 - loss: 0.5129 - val_Precision: 0.8099 - val_Recall: 0.6712 - val_accuracy: 0.7534 - val_loss: 0.5322
Epoch 27/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7558 - Recall: 0.6452 - accuracy: 0.7207 - loss: 0.6175 - val_Precision: 0.7899 - val_Recall: 0.6438 - val_accuracy: 0.7192 - val_loss: 0.5485
Epoch 28/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7886 - Recall: 0.6844 - accuracy: 0.7354 - loss: 0.5267 - val_Precision: 0.8120 - val_Recall: 0.6507 - val_accuracy: 0.7192 - val_loss: 0.5491
Epoch 29/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7912 - Recall: 0.6528 - accuracy: 0.7352 - loss: 0.5322 - val_Precision: 0.8182 - val_Recall: 0.6781 - val_accuracy: 0.7397 - val_loss: 0.5505
Epoch 30/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7637 - Recall: 0.6767 - accuracy: 0.7276 - loss: 0.5324 - val_Precision: 0.8348 - val_Recall: 0.6575 - val_accuracy: 0.7192 - val_loss: 0.5536
Epoch 31/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7862 - Recall: 0.6683 - accuracy: 0.7575 - loss: 0.5211 - val_Precision: 0.8250 - val_Recall: 0.6781 - val_accuracy: 0.7534 - val_loss: 0.5293
Epoch 32/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.8271 - Recall: 0.6603 - accuracy: 0.7743 - loss: 0.4825 - val_Precision: 0.8293 - val_Recall: 0.6986 - val_accuracy: 0.7260 - val_loss: 0.5010
Epoch 33/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.8311 - Recall: 0.7402 - accuracy: 0.7918 - loss: 0.4672 - val_Precision: 0.7984 - val_Recall: 0.7055 - val_accuracy: 0.7534 - val_loss: 0.5079
Epoch 34/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.8175 - Recall: 0.7375 - accuracy: 0.7802 - loss: 0.4893 - val_Precision: 0.8254 - val_Recall: 0.7123 - val_accuracy: 0.7466 - val_loss: 0.5057
Epoch 35/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7860 - Recall: 0.7104 - accuracy: 0.7516 - loss: 0.4551 - val_Precision: 0.8217 - val_Recall: 0.7260 - val_accuracy: 0.7603 - val_loss: 0.5073
Epoch 36/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.8130 - Recall: 0.7220 - accuracy: 0.7731 - loss: 0.4699 - val_Precision: 0.7829 - val_Recall: 0.6918 - val_accuracy: 0.7260 - val_loss: 0.5549
Epoch 37/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.8065 - Recall: 0.6949 - accuracy: 0.7556 - loss: 0.4824 - val_Precision: 0.8387 - val_Recall: 0.7123 - val_accuracy: 0.7534 - val_loss: 0.5048
Epoch 38/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - Precision: 0.7831 - Recall: 0.6593 - accuracy: 0.7537 - loss: 0.4768 - val_Precision: 0.8293 - val_Recall: 0.6986 - val_accuracy: 0.7534 - val_loss: 0.4940
Epoch 39/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7850 - Recall: 0.6854 - accuracy: 0.7379 - loss: 0.5276 - val_Precision: 0.8189 - val_Recall: 0.7123 - val_accuracy: 0.7466 - val_loss: 0.5344
Epoch 40/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7801 - Recall: 0.6677 - accuracy: 0.7268 - loss: 0.5463 - val_Precision: 0.8115 - val_Recall: 0.6781 - val_accuracy: 0.7397 - val_loss: 0.4913
Epoch 41/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.8324 - Recall: 0.7336 - accuracy: 0.7985 - loss: 0.4623 - val_Precision: 0.7874 - val_Recall: 0.6849 - val_accuracy: 0.7192 - val_loss: 0.4901
Epoch 42/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.8040 - Recall: 0.7287 - accuracy: 0.7732 - loss: 0.4738 - val_Precision: 0.8333 - val_Recall: 0.6849 - val_accuracy: 0.7603 - val_loss: 0.4771
Epoch 43/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.8312 - Recall: 0.7533 - accuracy: 0.7882 - loss: 0.4285 - val_Precision: 0.8115 - val_Recall: 0.6781 - val_accuracy: 0.7534 - val_loss: 0.4820
Epoch 44/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.7942 - Recall: 0.7099 - accuracy: 0.7634 - loss: 0.4811 - val_Precision: 0.7786 - val_Recall: 0.6986 - val_accuracy: 0.7055 - val_loss: 0.5135
Epoch 45/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - Precision: 0.7757 - Recall: 0.6941 - accuracy: 0.7504 - loss: 0.5041 - val_Precision: 0.7937 - val_Recall: 0.6849 - val_accuracy: 0.7397 - val_loss: 0.5132
Epoch 46/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.8215 - Recall: 0.7060 - accuracy: 0.7792 - loss: 0.4612 - val_Precision: 0.8160 - val_Recall: 0.6986 - val_accuracy: 0.7466 - val_loss: 0.5033
Epoch 47/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - Precision: 0.8198 - Recall: 0.7226 - accuracy: 0.7915 - loss: 0.4389 - val_Precision: 0.7812 - val_Recall: 0.6849 - val_accuracy: 0.7329 - val_loss: 0.5236
Epoch 48/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.7951 - Recall: 0.6979 - accuracy: 0.7569 - loss: 0.5131 - val_Precision: 0.8095 - val_Recall: 0.6986 - val_accuracy: 0.7534 - val_loss: 0.4927
Epoch 49/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - Precision: 0.8178 - Recall: 0.7295 - accuracy: 0.7618 - loss: 0.4797 - val_Precision: 0.7674 - val_Recall: 0.6781 - val_accuracy: 0.7329 - val_loss: 0.5109
Epoch 50/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - Precision: 0.7824 - Recall: 0.7248 - accuracy: 0.7593 - loss: 0.4685 - val_Precision: 0.7710 - val_Recall: 0.6918 - val_accuracy: 0.7260 - val_loss: 0.5161
Epoch 51/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - Precision: 0.7876 - Recall: 0.7022 - accuracy: 0.7511 - loss: 0.4606 - val_Precision: 0.7769 - val_Recall: 0.6918 - val_accuracy: 0.7260 - val_loss: 0.4966
Epoch 52/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step - Precision: 0.8367 - Recall: 0.7642 - accuracy: 0.8130 - loss: 0.4078 - val_Precision: 0.7630 - val_Recall: 0.7055 - val_accuracy: 0.7329 - val_loss: 0.5114

Predecimos para dicho modelo

from sklearn.metrics import classification_report, confusion_matrix, ConfusionMatrixDisplay
import numpy as np
import matplotlib.pyplot as plt

# Predicciones
y_test_pred_probs = best_model.predict(X_test_scaled)
y_test_pred_labels = np.argmax(y_test_pred_probs, axis=1)
y_test_true_labels = np.argmax(Y_test_onehot, axis=1)

# Reporte
print("Classification Report:")
print(classification_report(y_test_true_labels, y_test_pred_labels, digits=3))

# Matriz de confusión
class_names = ['Elephant', 'Rhino', 'Others']
cm = confusion_matrix(y_test_true_labels, y_test_pred_labels)
disp = ConfusionMatrixDisplay(confusion_matrix=cm, display_labels=class_names)
disp.plot(cmap='Blues')
plt.title("Confusion Matrix - Test Set")
plt.xlabel("Predicted label")
plt.ylabel("True label")
plt.grid(False)
plt.show()

5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 52ms/step
Classification Report:
              precision    recall  f1-score   support

           0      0.686     0.615     0.649        39
           1      0.535     0.657     0.590        35
           2      0.941     0.889     0.914        72

    accuracy                          0.760       146
   macro avg      0.721     0.720     0.718       146
weighted avg      0.776     0.760     0.766       146

Visualizamos predicciones en el test

import matplotlib.pyplot as plt
import numpy as np

# Número de ejemplos a mostrar
num_examples = 10
indices = np.random.choice(len(X_test_scaled), num_examples, replace=False)

# Nombres de clases
class_names = ['Elephant', 'Rhino', 'Others']

plt.figure(figsize=(12, 6 * num_examples // 3))

for i, idx in enumerate(indices):
    img = imgs_test[idx]
    mask = masks_test[idx]  
    true_label = y_test[idx]
    pred_label = y_test_pred_labels[idx]

    color = 'green' if true_label == pred_label else 'red'

    # Imagen original
    plt.subplot(num_examples, 2, 2 * i + 1)
    plt.imshow(img)
    plt.axis('off')
    plt.title(f"[IMG] Real: {class_names[true_label]} | Pred: {class_names[pred_label]}", color=color)

    # Máscara binaria
    plt.subplot(num_examples, 2, 2 * i + 2)
    plt.imshow(mask, cmap='gray')
    plt.axis('off')
    plt.title(f"[MASK] Figura binaria", color=color)

plt.suptitle("Predicciones del modelo con forma (máscara) incluida", fontsize=18)
plt.tight_layout()
plt.show()

Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers). Got range [-0.11641828..1.0890203].

Ahora, para ver si hay diferencias, entrenamos el modelo solo con los canales RGB y el contorno

from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from tensorflow.keras.utils import to_categorical

# Solo RGB figura (3), RGB fondo (3), contorno área (1) = 7 características
X_rgb_contour = X[:, :7]

X_train_rc, X_test_rc, y_train_rc, y_test_rc, imgs_train_rc, imgs_test_rc, masks_train_rc, masks_test_rc = train_test_split(
    X_rgb_contour, etiquetas_aug, imagenes_aug, mascaras_aug, test_size=0.2, random_state=42
)

# Escalado
scaler_rc = StandardScaler()
X_train_rc_scaled = scaler_rc.fit_transform(X_train_rc)
X_test_rc_scaled = scaler_rc.transform(X_test_rc)

# One-hot encoding
y_train_rc = y_train_rc.astype("int32")
y_test_rc = y_test_rc.astype("int32")

Y_train_rc_onehot = to_categorical(y_train_rc, num_classes=4).astype("float32")
Y_test_rc_onehot = to_categorical(y_test_rc, num_classes=4).astype("float32")

from keras.models import Sequential
from keras.layers import Dense, Dropout, BatchNormalization, Input
from keras.optimizers import Adam

model_rgb_contour = Sequential([
    Input(shape=(7,)),  # Solo 7 características ahora
    Dense(256, activation='relu'),
    BatchNormalization(),
    Dropout(0.4),

    Dense(128, activation='tanh'),
    Dropout(0.4),

    Dense(64, activation='relu'),
    Dropout(0.4),

    Dense(32, activation='relu'),
    Dropout(0.4),

    Dense(16, activation='relu'),
    Dense(4, activation='softmax')
])

model_rgb_contour.compile(
    optimizer=Adam(learning_rate=0.001),
    loss='categorical_crossentropy',
    metrics=['accuracy', 'Precision', 'Recall', 'AUC']
)

history_rc = model_rgb_contour.fit(
    X_train_rc_scaled,
    Y_train_rc_onehot,
    validation_data=(X_test_rc_scaled, Y_test_rc_onehot),
    epochs=100,
    batch_size=16,
    verbose=1
)

Epoch 1/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 9s 38ms/step - AUC: 0.5404 - Precision: 0.3289 - Recall: 0.1348 - accuracy: 0.3484 - loss: 1.6884 - val_AUC: 0.9020 - val_Precision: 1.0000 - val_Recall: 0.0274 - val_accuracy: 0.6575 - val_loss: 1.1638
Epoch 2/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 1s 15ms/step - AUC: 0.8334 - Precision: 0.7109 - Recall: 0.3905 - accuracy: 0.6038 - loss: 0.9896 - val_AUC: 0.9293 - val_Precision: 1.0000 - val_Recall: 0.2877 - val_accuracy: 0.6575 - val_loss: 0.9294
Epoch 3/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.8618 - Precision: 0.6718 - Recall: 0.4973 - accuracy: 0.6103 - loss: 0.8734 - val_AUC: 0.9346 - val_Precision: 1.0000 - val_Recall: 0.4041 - val_accuracy: 0.6986 - val_loss: 0.7918
Epoch 4/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.8711 - Precision: 0.6632 - Recall: 0.4816 - accuracy: 0.5918 - loss: 0.8621 - val_AUC: 0.9332 - val_Precision: 1.0000 - val_Recall: 0.4521 - val_accuracy: 0.7055 - val_loss: 0.7054
Epoch 5/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8980 - Precision: 0.7278 - Recall: 0.5781 - accuracy: 0.6735 - loss: 0.7737 - val_AUC: 0.9417 - val_Precision: 1.0000 - val_Recall: 0.4726 - val_accuracy: 0.7534 - val_loss: 0.6505
Epoch 6/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8816 - Precision: 0.6800 - Recall: 0.5264 - accuracy: 0.6129 - loss: 0.8142 - val_AUC: 0.9389 - val_Precision: 0.9733 - val_Recall: 0.5000 - val_accuracy: 0.7260 - val_loss: 0.6261
Epoch 7/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9120 - Precision: 0.7436 - Recall: 0.5613 - accuracy: 0.6789 - loss: 0.6863 - val_AUC: 0.9347 - val_Precision: 0.8690 - val_Recall: 0.5000 - val_accuracy: 0.6918 - val_loss: 0.5991
Epoch 8/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9044 - Precision: 0.7393 - Recall: 0.5729 - accuracy: 0.6890 - loss: 0.7368 - val_AUC: 0.9376 - val_Precision: 0.8706 - val_Recall: 0.5068 - val_accuracy: 0.7329 - val_loss: 0.5891
Epoch 9/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9052 - Precision: 0.6993 - Recall: 0.5429 - accuracy: 0.6603 - loss: 0.7014 - val_AUC: 0.9316 - val_Precision: 0.8706 - val_Recall: 0.5068 - val_accuracy: 0.7260 - val_loss: 0.5872
Epoch 10/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9093 - Precision: 0.7196 - Recall: 0.5509 - accuracy: 0.6591 - loss: 0.6864 - val_AUC: 0.9399 - val_Precision: 0.8421 - val_Recall: 0.5479 - val_accuracy: 0.7603 - val_loss: 0.5499
Epoch 11/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9283 - Precision: 0.7455 - Recall: 0.5950 - accuracy: 0.7090 - loss: 0.6190 - val_AUC: 0.9327 - val_Precision: 0.7265 - val_Recall: 0.5822 - val_accuracy: 0.6986 - val_loss: 0.5686
Epoch 12/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9218 - Precision: 0.7593 - Recall: 0.5778 - accuracy: 0.6882 - loss: 0.6337 - val_AUC: 0.9339 - val_Precision: 0.7864 - val_Recall: 0.5548 - val_accuracy: 0.7192 - val_loss: 0.5728
Epoch 13/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.8965 - Precision: 0.6967 - Recall: 0.5145 - accuracy: 0.6267 - loss: 0.7293 - val_AUC: 0.9429 - val_Precision: 0.8155 - val_Recall: 0.5753 - val_accuracy: 0.7534 - val_loss: 0.5455
Epoch 14/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9101 - Precision: 0.7378 - Recall: 0.5630 - accuracy: 0.6755 - loss: 0.6729 - val_AUC: 0.9398 - val_Precision: 0.8095 - val_Recall: 0.5822 - val_accuracy: 0.7397 - val_loss: 0.5334
Epoch 15/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9150 - Precision: 0.7746 - Recall: 0.5984 - accuracy: 0.6779 - loss: 0.6765 - val_AUC: 0.9381 - val_Precision: 0.8333 - val_Recall: 0.5479 - val_accuracy: 0.7260 - val_loss: 0.5495
Epoch 16/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9167 - Precision: 0.7361 - Recall: 0.5619 - accuracy: 0.6546 - loss: 0.6513 - val_AUC: 0.9286 - val_Precision: 0.7131 - val_Recall: 0.5959 - val_accuracy: 0.6849 - val_loss: 0.5835
Epoch 17/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9161 - Precision: 0.7456 - Recall: 0.5804 - accuracy: 0.6757 - loss: 0.6728 - val_AUC: 0.9414 - val_Precision: 0.8208 - val_Recall: 0.5959 - val_accuracy: 0.7123 - val_loss: 0.5442
Epoch 18/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9201 - Precision: 0.7585 - Recall: 0.5618 - accuracy: 0.7011 - loss: 0.6376 - val_AUC: 0.9441 - val_Precision: 0.8018 - val_Recall: 0.6096 - val_accuracy: 0.7329 - val_loss: 0.5310
Epoch 19/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.9278 - Precision: 0.7615 - Recall: 0.5962 - accuracy: 0.7011 - loss: 0.6158 - val_AUC: 0.9453 - val_Precision: 0.7931 - val_Recall: 0.6301 - val_accuracy: 0.7260 - val_loss: 0.5243
Epoch 20/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 1s 13ms/step - AUC: 0.9262 - Precision: 0.7403 - Recall: 0.5869 - accuracy: 0.6874 - loss: 0.6196 - val_AUC: 0.9366 - val_Precision: 0.7373 - val_Recall: 0.5959 - val_accuracy: 0.7260 - val_loss: 0.5433
Epoch 21/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.9236 - Precision: 0.7545 - Recall: 0.5970 - accuracy: 0.6838 - loss: 0.6242 - val_AUC: 0.9484 - val_Precision: 0.7833 - val_Recall: 0.6438 - val_accuracy: 0.7466 - val_loss: 0.5177
Epoch 22/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9325 - Precision: 0.7962 - Recall: 0.6507 - accuracy: 0.7052 - loss: 0.5894 - val_AUC: 0.9416 - val_Precision: 0.7672 - val_Recall: 0.6096 - val_accuracy: 0.7603 - val_loss: 0.5345
Epoch 23/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9432 - Precision: 0.7956 - Recall: 0.6611 - accuracy: 0.7446 - loss: 0.5452 - val_AUC: 0.9404 - val_Precision: 0.7845 - val_Recall: 0.6233 - val_accuracy: 0.7329 - val_loss: 0.5474
Epoch 24/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 1s 12ms/step - AUC: 0.9387 - Precision: 0.7907 - Recall: 0.6673 - accuracy: 0.7322 - loss: 0.5679 - val_AUC: 0.9418 - val_Precision: 0.7583 - val_Recall: 0.6233 - val_accuracy: 0.7260 - val_loss: 0.5404
Epoch 25/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9371 - Precision: 0.7892 - Recall: 0.6608 - accuracy: 0.7284 - loss: 0.5698 - val_AUC: 0.9476 - val_Precision: 0.8198 - val_Recall: 0.6233 - val_accuracy: 0.7808 - val_loss: 0.5204
Epoch 26/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9271 - Precision: 0.7664 - Recall: 0.6193 - accuracy: 0.7083 - loss: 0.6010 - val_AUC: 0.9485 - val_Precision: 0.8246 - val_Recall: 0.6438 - val_accuracy: 0.7466 - val_loss: 0.5184
Epoch 27/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 11ms/step - AUC: 0.9183 - Precision: 0.7467 - Recall: 0.6055 - accuracy: 0.6898 - loss: 0.6563 - val_AUC: 0.9469 - val_Precision: 0.8190 - val_Recall: 0.6507 - val_accuracy: 0.7534 - val_loss: 0.5260
Epoch 28/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.9409 - Precision: 0.8014 - Recall: 0.6552 - accuracy: 0.7260 - loss: 0.5631 - val_AUC: 0.9523 - val_Precision: 0.8017 - val_Recall: 0.6644 - val_accuracy: 0.7740 - val_loss: 0.4996
Epoch 29/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.9295 - Precision: 0.7447 - Recall: 0.6125 - accuracy: 0.6815 - loss: 0.5989 - val_AUC: 0.9447 - val_Precision: 0.7984 - val_Recall: 0.6781 - val_accuracy: 0.7603 - val_loss: 0.5157
Epoch 30/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9401 - Precision: 0.7830 - Recall: 0.6795 - accuracy: 0.7411 - loss: 0.5648 - val_AUC: 0.9515 - val_Precision: 0.7881 - val_Recall: 0.6370 - val_accuracy: 0.7671 - val_loss: 0.5006
Epoch 31/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9290 - Precision: 0.7714 - Recall: 0.6222 - accuracy: 0.7224 - loss: 0.6152 - val_AUC: 0.9519 - val_Precision: 0.8190 - val_Recall: 0.6507 - val_accuracy: 0.7603 - val_loss: 0.5089
Epoch 32/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9273 - Precision: 0.7530 - Recall: 0.6045 - accuracy: 0.6838 - loss: 0.6186 - val_AUC: 0.9523 - val_Precision: 0.8160 - val_Recall: 0.6986 - val_accuracy: 0.8014 - val_loss: 0.5004
Epoch 33/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 1s 13ms/step - AUC: 0.9449 - Precision: 0.7995 - Recall: 0.6689 - accuracy: 0.7421 - loss: 0.5536 - val_AUC: 0.9490 - val_Precision: 0.8000 - val_Recall: 0.6849 - val_accuracy: 0.7808 - val_loss: 0.5285
Epoch 34/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 11ms/step - AUC: 0.9516 - Precision: 0.8225 - Recall: 0.7239 - accuracy: 0.7787 - loss: 0.5069 - val_AUC: 0.9485 - val_Precision: 0.7795 - val_Recall: 0.6781 - val_accuracy: 0.7329 - val_loss: 0.5131
Epoch 35/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9395 - Precision: 0.7909 - Recall: 0.6913 - accuracy: 0.7470 - loss: 0.5671 - val_AUC: 0.9471 - val_Precision: 0.8017 - val_Recall: 0.6644 - val_accuracy: 0.7397 - val_loss: 0.5216
Epoch 36/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9405 - Precision: 0.7744 - Recall: 0.6629 - accuracy: 0.7166 - loss: 0.5603 - val_AUC: 0.9518 - val_Precision: 0.8000 - val_Recall: 0.6849 - val_accuracy: 0.7740 - val_loss: 0.5058
Epoch 37/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9382 - Precision: 0.7628 - Recall: 0.6651 - accuracy: 0.7166 - loss: 0.5661 - val_AUC: 0.9497 - val_Precision: 0.8033 - val_Recall: 0.6712 - val_accuracy: 0.7671 - val_loss: 0.5242
Epoch 38/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9379 - Precision: 0.7842 - Recall: 0.6390 - accuracy: 0.7256 - loss: 0.5701 - val_AUC: 0.9493 - val_Precision: 0.8049 - val_Recall: 0.6781 - val_accuracy: 0.7808 - val_loss: 0.5234
Epoch 39/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.9455 - Precision: 0.8162 - Recall: 0.6993 - accuracy: 0.7683 - loss: 0.5497 - val_AUC: 0.9510 - val_Precision: 0.7923 - val_Recall: 0.7055 - val_accuracy: 0.7740 - val_loss: 0.5185
Epoch 40/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9362 - Precision: 0.7584 - Recall: 0.6611 - accuracy: 0.7142 - loss: 0.5793 - val_AUC: 0.9538 - val_Precision: 0.8203 - val_Recall: 0.7192 - val_accuracy: 0.7877 - val_loss: 0.5023
Epoch 41/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9362 - Precision: 0.7873 - Recall: 0.6642 - accuracy: 0.7399 - loss: 0.6026 - val_AUC: 0.9506 - val_Precision: 0.8017 - val_Recall: 0.6644 - val_accuracy: 0.7671 - val_loss: 0.5059
Epoch 42/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.9343 - Precision: 0.7748 - Recall: 0.6597 - accuracy: 0.7454 - loss: 0.5801 - val_AUC: 0.9433 - val_Precision: 0.7698 - val_Recall: 0.6644 - val_accuracy: 0.7534 - val_loss: 0.5334
Epoch 43/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9378 - Precision: 0.8204 - Recall: 0.6776 - accuracy: 0.7541 - loss: 0.5988 - val_AUC: 0.9539 - val_Precision: 0.8115 - val_Recall: 0.6781 - val_accuracy: 0.7945 - val_loss: 0.5157
Epoch 44/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 11ms/step - AUC: 0.9329 - Precision: 0.7994 - Recall: 0.6779 - accuracy: 0.7294 - loss: 0.6069 - val_AUC: 0.9435 - val_Precision: 0.7712 - val_Recall: 0.6233 - val_accuracy: 0.7466 - val_loss: 0.5460
Epoch 45/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.9403 - Precision: 0.7765 - Recall: 0.6652 - accuracy: 0.7211 - loss: 0.5692 - val_AUC: 0.9601 - val_Precision: 0.8417 - val_Recall: 0.6918 - val_accuracy: 0.7808 - val_loss: 0.4804
Epoch 46/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9400 - Precision: 0.7749 - Recall: 0.6768 - accuracy: 0.7355 - loss: 0.5689 - val_AUC: 0.9591 - val_Precision: 0.8636 - val_Recall: 0.6507 - val_accuracy: 0.8219 - val_loss: 0.4860
Epoch 47/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9238 - Precision: 0.7375 - Recall: 0.6453 - accuracy: 0.7094 - loss: 0.6422 - val_AUC: 0.9558 - val_Precision: 0.8649 - val_Recall: 0.6575 - val_accuracy: 0.7945 - val_loss: 0.4848
Epoch 48/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.9369 - Precision: 0.7983 - Recall: 0.6476 - accuracy: 0.7473 - loss: 0.5790 - val_AUC: 0.9537 - val_Precision: 0.8197 - val_Recall: 0.6849 - val_accuracy: 0.8082 - val_loss: 0.4971
Epoch 49/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9424 - Precision: 0.7630 - Recall: 0.6614 - accuracy: 0.7445 - loss: 0.5475 - val_AUC: 0.9547 - val_Precision: 0.8264 - val_Recall: 0.6849 - val_accuracy: 0.8014 - val_loss: 0.5012
Epoch 50/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9345 - Precision: 0.7397 - Recall: 0.6646 - accuracy: 0.7178 - loss: 0.5751 - val_AUC: 0.9580 - val_Precision: 0.8320 - val_Recall: 0.7123 - val_accuracy: 0.8151 - val_loss: 0.4876
Epoch 51/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9398 - Precision: 0.7817 - Recall: 0.6735 - accuracy: 0.7399 - loss: 0.5703 - val_AUC: 0.9549 - val_Precision: 0.8217 - val_Recall: 0.7260 - val_accuracy: 0.8151 - val_loss: 0.4997
Epoch 52/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.9466 - Precision: 0.8011 - Recall: 0.7116 - accuracy: 0.7580 - loss: 0.5277 - val_AUC: 0.9578 - val_Precision: 0.8333 - val_Recall: 0.6849 - val_accuracy: 0.8014 - val_loss: 0.4903
Epoch 53/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9286 - Precision: 0.7357 - Recall: 0.6328 - accuracy: 0.7047 - loss: 0.6131 - val_AUC: 0.9603 - val_Precision: 0.8500 - val_Recall: 0.6986 - val_accuracy: 0.8151 - val_loss: 0.4798
Epoch 54/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9344 - Precision: 0.7560 - Recall: 0.6392 - accuracy: 0.7181 - loss: 0.5731 - val_AUC: 0.9603 - val_Precision: 0.8417 - val_Recall: 0.6918 - val_accuracy: 0.8082 - val_loss: 0.4812
Epoch 55/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.9281 - Precision: 0.7613 - Recall: 0.6580 - accuracy: 0.7161 - loss: 0.6292 - val_AUC: 0.9618 - val_Precision: 0.8607 - val_Recall: 0.7192 - val_accuracy: 0.8082 - val_loss: 0.4737
Epoch 56/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9519 - Precision: 0.7998 - Recall: 0.6917 - accuracy: 0.7576 - loss: 0.4941 - val_AUC: 0.9563 - val_Precision: 0.8160 - val_Recall: 0.6986 - val_accuracy: 0.7808 - val_loss: 0.4883
Epoch 57/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9398 - Precision: 0.7747 - Recall: 0.6798 - accuracy: 0.7255 - loss: 0.5560 - val_AUC: 0.9616 - val_Precision: 0.8400 - val_Recall: 0.7192 - val_accuracy: 0.8082 - val_loss: 0.4687
Epoch 58/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.9446 - Precision: 0.7764 - Recall: 0.6791 - accuracy: 0.7385 - loss: 0.5325 - val_AUC: 0.9623 - val_Precision: 0.8189 - val_Recall: 0.7123 - val_accuracy: 0.8014 - val_loss: 0.4643
Epoch 59/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9453 - Precision: 0.8092 - Recall: 0.7043 - accuracy: 0.7634 - loss: 0.5364 - val_AUC: 0.9631 - val_Precision: 0.8374 - val_Recall: 0.7055 - val_accuracy: 0.8151 - val_loss: 0.4629
Epoch 60/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.9479 - Precision: 0.8096 - Recall: 0.6999 - accuracy: 0.7577 - loss: 0.5270 - val_AUC: 0.9612 - val_Precision: 0.8548 - val_Recall: 0.7260 - val_accuracy: 0.8425 - val_loss: 0.4776
Epoch 61/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9608 - Precision: 0.8177 - Recall: 0.7333 - accuracy: 0.7912 - loss: 0.4544 - val_AUC: 0.9640 - val_Precision: 0.8450 - val_Recall: 0.7466 - val_accuracy: 0.8219 - val_loss: 0.4543
Epoch 62/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 12ms/step - AUC: 0.9350 - Precision: 0.7699 - Recall: 0.6774 - accuracy: 0.7093 - loss: 0.5891 - val_AUC: 0.9656 - val_Precision: 0.8770 - val_Recall: 0.7329 - val_accuracy: 0.8356 - val_loss: 0.4557
Epoch 63/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9497 - Precision: 0.7887 - Recall: 0.6904 - accuracy: 0.7540 - loss: 0.5042 - val_AUC: 0.9674 - val_Precision: 0.8548 - val_Recall: 0.7260 - val_accuracy: 0.8151 - val_loss: 0.4488
Epoch 64/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.9539 - Precision: 0.8047 - Recall: 0.7089 - accuracy: 0.7584 - loss: 0.4822 - val_AUC: 0.9595 - val_Precision: 0.8168 - val_Recall: 0.7329 - val_accuracy: 0.7945 - val_loss: 0.4657
Epoch 65/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9446 - Precision: 0.7922 - Recall: 0.6803 - accuracy: 0.7394 - loss: 0.5371 - val_AUC: 0.9655 - val_Precision: 0.8496 - val_Recall: 0.7740 - val_accuracy: 0.8288 - val_loss: 0.4424
Epoch 66/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.9432 - Precision: 0.7950 - Recall: 0.6832 - accuracy: 0.7527 - loss: 0.5508 - val_AUC: 0.9627 - val_Precision: 0.8583 - val_Recall: 0.7466 - val_accuracy: 0.8356 - val_loss: 0.4711
Epoch 67/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.9457 - Precision: 0.7706 - Recall: 0.6735 - accuracy: 0.7494 - loss: 0.5255 - val_AUC: 0.9677 - val_Precision: 0.8710 - val_Recall: 0.7397 - val_accuracy: 0.8356 - val_loss: 0.4450
Epoch 68/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 9ms/step - AUC: 0.9562 - Precision: 0.8160 - Recall: 0.7086 - accuracy: 0.7867 - loss: 0.4877 - val_AUC: 0.9672 - val_Precision: 0.8682 - val_Recall: 0.7671 - val_accuracy: 0.8219 - val_loss: 0.4525
Epoch 69/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9548 - Precision: 0.8274 - Recall: 0.7286 - accuracy: 0.7904 - loss: 0.4950 - val_AUC: 0.9648 - val_Precision: 0.8730 - val_Recall: 0.7534 - val_accuracy: 0.8356 - val_loss: 0.4622
Epoch 70/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9557 - Precision: 0.8247 - Recall: 0.6965 - accuracy: 0.7859 - loss: 0.4921 - val_AUC: 0.9656 - val_Precision: 0.8561 - val_Recall: 0.7740 - val_accuracy: 0.8219 - val_loss: 0.4453
Epoch 71/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9553 - Precision: 0.8118 - Recall: 0.7229 - accuracy: 0.7860 - loss: 0.4852 - val_AUC: 0.9669 - val_Precision: 0.8702 - val_Recall: 0.7808 - val_accuracy: 0.8493 - val_loss: 0.4431
Epoch 72/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 11ms/step - AUC: 0.9621 - Precision: 0.8357 - Recall: 0.7441 - accuracy: 0.7922 - loss: 0.4469 - val_AUC: 0.9675 - val_Precision: 0.8593 - val_Recall: 0.7945 - val_accuracy: 0.8288 - val_loss: 0.4312
Epoch 73/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9539 - Precision: 0.7920 - Recall: 0.7056 - accuracy: 0.7597 - loss: 0.4918 - val_AUC: 0.9567 - val_Precision: 0.8160 - val_Recall: 0.6986 - val_accuracy: 0.8082 - val_loss: 0.4683
Epoch 74/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9497 - Precision: 0.7675 - Recall: 0.7080 - accuracy: 0.7455 - loss: 0.4972 - val_AUC: 0.9693 - val_Precision: 0.8769 - val_Recall: 0.7808 - val_accuracy: 0.8356 - val_loss: 0.4432
Epoch 75/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9567 - Precision: 0.8156 - Recall: 0.7385 - accuracy: 0.7776 - loss: 0.4755 - val_AUC: 0.9685 - val_Precision: 0.8769 - val_Recall: 0.7808 - val_accuracy: 0.8630 - val_loss: 0.4354
Epoch 76/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9616 - Precision: 0.8241 - Recall: 0.7537 - accuracy: 0.7940 - loss: 0.4523 - val_AUC: 0.9659 - val_Precision: 0.8643 - val_Recall: 0.8288 - val_accuracy: 0.8630 - val_loss: 0.4444
Epoch 77/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9502 - Precision: 0.8209 - Recall: 0.7376 - accuracy: 0.7901 - loss: 0.5363 - val_AUC: 0.9701 - val_Precision: 0.8712 - val_Recall: 0.7877 - val_accuracy: 0.8630 - val_loss: 0.4359
Epoch 78/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9578 - Precision: 0.8338 - Recall: 0.7351 - accuracy: 0.7772 - loss: 0.4655 - val_AUC: 0.9704 - val_Precision: 0.8741 - val_Recall: 0.8082 - val_accuracy: 0.8493 - val_loss: 0.4189
Epoch 79/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.9538 - Precision: 0.8207 - Recall: 0.7405 - accuracy: 0.7826 - loss: 0.5001 - val_AUC: 0.9660 - val_Precision: 0.8519 - val_Recall: 0.7877 - val_accuracy: 0.8288 - val_loss: 0.4490
Epoch 80/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9553 - Precision: 0.8077 - Recall: 0.7247 - accuracy: 0.7671 - loss: 0.4771 - val_AUC: 0.9641 - val_Precision: 0.8633 - val_Recall: 0.8219 - val_accuracy: 0.8562 - val_loss: 0.4581
Epoch 81/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9599 - Precision: 0.8331 - Recall: 0.7791 - accuracy: 0.8206 - loss: 0.4606 - val_AUC: 0.9721 - val_Precision: 0.8971 - val_Recall: 0.8356 - val_accuracy: 0.8767 - val_loss: 0.4118
Epoch 82/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 10ms/step - AUC: 0.9477 - Precision: 0.7712 - Recall: 0.7068 - accuracy: 0.7385 - loss: 0.5237 - val_AUC: 0.9734 - val_Precision: 0.9051 - val_Recall: 0.8493 - val_accuracy: 0.8904 - val_loss: 0.4075
Epoch 83/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9576 - Precision: 0.8260 - Recall: 0.7454 - accuracy: 0.7901 - loss: 0.4705 - val_AUC: 0.9727 - val_Precision: 0.9000 - val_Recall: 0.8630 - val_accuracy: 0.8836 - val_loss: 0.4261
Epoch 84/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9534 - Precision: 0.8057 - Recall: 0.7216 - accuracy: 0.7653 - loss: 0.4835 - val_AUC: 0.9747 - val_Precision: 0.8986 - val_Recall: 0.8493 - val_accuracy: 0.8767 - val_loss: 0.4055
Epoch 85/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9529 - Precision: 0.7889 - Recall: 0.7285 - accuracy: 0.7715 - loss: 0.4951 - val_AUC: 0.9701 - val_Precision: 0.8615 - val_Recall: 0.7671 - val_accuracy: 0.8493 - val_loss: 0.4238
Epoch 86/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9498 - Precision: 0.8152 - Recall: 0.7270 - accuracy: 0.7807 - loss: 0.5498 - val_AUC: 0.9771 - val_Precision: 0.9015 - val_Recall: 0.8151 - val_accuracy: 0.8630 - val_loss: 0.3960
Epoch 87/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 5ms/step - AUC: 0.9548 - Precision: 0.8271 - Recall: 0.7244 - accuracy: 0.7717 - loss: 0.5021 - val_AUC: 0.9760 - val_Precision: 0.8955 - val_Recall: 0.8219 - val_accuracy: 0.8699 - val_loss: 0.3971
Epoch 88/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 8ms/step - AUC: 0.9551 - Precision: 0.8255 - Recall: 0.7307 - accuracy: 0.8013 - loss: 0.4938 - val_AUC: 0.9778 - val_Precision: 0.9030 - val_Recall: 0.8288 - val_accuracy: 0.8836 - val_loss: 0.3855
Epoch 89/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9546 - Precision: 0.8282 - Recall: 0.7364 - accuracy: 0.7980 - loss: 0.5010 - val_AUC: 0.9741 - val_Precision: 0.9058 - val_Recall: 0.8562 - val_accuracy: 0.8699 - val_loss: 0.3917
Epoch 90/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9396 - Precision: 0.7844 - Recall: 0.6962 - accuracy: 0.7463 - loss: 0.5790 - val_AUC: 0.9770 - val_Precision: 0.8931 - val_Recall: 0.8014 - val_accuracy: 0.8767 - val_loss: 0.3964
Epoch 91/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9530 - Precision: 0.8127 - Recall: 0.7302 - accuracy: 0.7812 - loss: 0.5080 - val_AUC: 0.9701 - val_Precision: 0.8759 - val_Recall: 0.8219 - val_accuracy: 0.8630 - val_loss: 0.4166
Epoch 92/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9597 - Precision: 0.8362 - Recall: 0.7582 - accuracy: 0.8033 - loss: 0.4707 - val_AUC: 0.9743 - val_Precision: 0.8626 - val_Recall: 0.7740 - val_accuracy: 0.8493 - val_loss: 0.4056
Epoch 93/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9615 - Precision: 0.8208 - Recall: 0.7229 - accuracy: 0.7995 - loss: 0.4439 - val_AUC: 0.9746 - val_Precision: 0.8855 - val_Recall: 0.7945 - val_accuracy: 0.8562 - val_loss: 0.4144
Epoch 94/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9584 - Precision: 0.8372 - Recall: 0.7267 - accuracy: 0.7896 - loss: 0.4785 - val_AUC: 0.9739 - val_Precision: 0.8872 - val_Recall: 0.8082 - val_accuracy: 0.8699 - val_loss: 0.4048
Epoch 95/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9610 - Precision: 0.8607 - Recall: 0.7820 - accuracy: 0.8231 - loss: 0.4603 - val_AUC: 0.9755 - val_Precision: 0.8889 - val_Recall: 0.8219 - val_accuracy: 0.8836 - val_loss: 0.4031
Epoch 96/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 11ms/step - AUC: 0.9561 - Precision: 0.8110 - Recall: 0.7429 - accuracy: 0.7820 - loss: 0.4803 - val_AUC: 0.9732 - val_Precision: 0.8963 - val_Recall: 0.8288 - val_accuracy: 0.8767 - val_loss: 0.3992
Epoch 97/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9609 - Precision: 0.8306 - Recall: 0.7559 - accuracy: 0.7966 - loss: 0.4662 - val_AUC: 0.9692 - val_Precision: 0.8692 - val_Recall: 0.7740 - val_accuracy: 0.8493 - val_loss: 0.4170
Epoch 98/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9643 - Precision: 0.8520 - Recall: 0.7605 - accuracy: 0.8078 - loss: 0.4363 - val_AUC: 0.9728 - val_Precision: 0.8881 - val_Recall: 0.8151 - val_accuracy: 0.8493 - val_loss: 0.4125
Epoch 99/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 6ms/step - AUC: 0.9541 - Precision: 0.8060 - Recall: 0.7564 - accuracy: 0.7809 - loss: 0.4989 - val_AUC: 0.9727 - val_Precision: 0.9037 - val_Recall: 0.8356 - val_accuracy: 0.8630 - val_loss: 0.4216
Epoch 100/100
37/37 ━━━━━━━━━━━━━━━━━━━━ 0s 7ms/step - AUC: 0.9730 - Precision: 0.8528 - Recall: 0.7787 - accuracy: 0.8232 - loss: 0.3842 - val_AUC: 0.9759 - val_Precision: 0.8955 - val_Recall: 0.8219 - val_accuracy: 0.8699 - val_loss: 0.3887

from sklearn.metrics import classification_report, confusion_matrix, ConfusionMatrixDisplay
import matplotlib.pyplot as plt
import numpy as np

# Predicciones del modelo
y_pred_probs_rc = model_rgb_contour.predict(X_test_rc_scaled)
y_pred_labels_rc = np.argmax(y_pred_probs_rc, axis=1)
y_true_labels_rc = np.argmax(Y_test_rc_onehot, axis=1)

# Reporte de clasificación
print("Clasification Report (solo RGB + contorno):")
print(classification_report(y_true_labels_rc, y_pred_labels_rc, digits=4))

# Matriz de confusión
cm_rc = confusion_matrix(y_true_labels_rc, y_pred_labels_rc)
disp_rc = ConfusionMatrixDisplay(confusion_matrix=cm_rc)
disp_rc.plot(cmap='Purples')
plt.title("Matriz de confusión - Modelo RGB + contorno")
plt.grid(False)
plt.show()

5/5 ━━━━━━━━━━━━━━━━━━━━ 0s 42ms/step
Clasification Report (solo RGB + contorno):
              precision    recall  f1-score   support

           0     0.7500    0.9231    0.8276        39
           1     0.7368    0.5385    0.6222        26
           2     0.9747    0.9506    0.9625        81

    accuracy                         0.8699       146
   macro avg     0.8205    0.8041    0.8041       146
weighted avg     0.8723    0.8699    0.8659       146

import matplotlib.pyplot as plt
import numpy as np

# Número de ejemplos a mostrar
num_examples = 10

# Selección aleatoria de índices del conjunto de test
indices_rc = np.random.choice(len(X_test_rc), num_examples, replace=False)

# Nombres de las clases (deben coincidir con tu codificación)
class_names = ['Elephant', 'Rhino', 'Others']

# Figura general
plt.figure(figsize=(12, 6 * num_examples // 3))

for i, idx in enumerate(indices_rc):
    img = imgs_test_rc[idx]                    
    mask = masks_test_rc[idx]                  # Máscara correspondiente
    true_label = int(y_test_rc[idx])           # Etiqueta real como entero
    pred_label = int(y_pred_labels_rc[idx])    # Etiqueta predicha

    color = 'green' if true_label == pred_label else 'red'  # Color del texto según acierto

    # Evitar problemas con valores fuera de rango [0,1]
    img_clipped = np.clip(img, 0.0, 1.0)

    # Mostrar imagen original
    plt.subplot(num_examples, 2, 2 * i + 1)
    plt.imshow(img_clipped)
    plt.axis('off')
    plt.title(f"[IMG] Real: {class_names[true_label]} | Pred: {class_names[pred_label]}", color=color)

    # Mostrar máscara binaria
    plt.subplot(num_examples, 2, 2 * i + 2)
    plt.imshow(mask, cmap='gray')
    plt.axis('off')
    plt.title("[MASK] Figura binaria", color=color)

plt.suptitle("Predicciones (modelo RGB + contorno)", fontsize=18)
plt.tight_layout()
plt.show()

Comparación de métricas

import matplotlib.pyplot as plt
import numpy as np

# Métricas del modelo completo
metrics_full = {
    "Accuracy": accuracy_score(y_test_true_labels, y_test_pred_labels),
    "Precision": precision_score(y_test_true_labels, y_test_pred_labels, average='macro', zero_division=0.0),
    "Recall": recall_score(y_test_true_labels, y_test_pred_labels, average='macro'),
    "F1 Score": f1_score(y_test_true_labels, y_test_pred_labels, average='macro'),
}

# Métricas del modelo RGB + contorno
metrics_rgbc = {
    "Accuracy": accuracy_score(y_true_labels_rc, y_pred_labels_rc),
    "Precision": precision_score(y_true_labels_rc, y_pred_labels_rc, average='macro', zero_division=0.0),
    "Recall": recall_score(y_true_labels_rc, y_pred_labels_rc, average='macro'),
    "F1 Score": f1_score(y_true_labels_rc, y_pred_labels_rc, average='macro'),
}

# Preparar gráfico
metric_names = list(metrics_full.keys())
val_full = [metrics_full[m] for m in metric_names]
val_rgbc = [metrics_rgbc[m] for m in metric_names]

x = np.arange(len(metric_names))
width = 0.35

# Plot
plt.figure(figsize=(10, 6))
plt.bar(x - width/2, val_full, width, label='Modelo completo')
plt.bar(x + width/2, val_rgbc, width, label='RGB + contorno')

plt.xticks(x, metric_names)
plt.ylim(0, 1.05)
plt.ylabel('Score')
plt.title('Comparación de métricas entre modelos')
plt.legend()
plt.grid(axis='y', linestyle='--', alpha=0.6)
plt.tight_layout()
plt.show()